• Build a high performing team through coaching, mentoring, clear direction, and effective management
• Ensure that the team is working in a common way, aligned with peers and the wider DTA and that there is a clear understanding of the role play
• Management of team's workload and priorities, providing clear visibility, ensuring the right resource available to work within squads - based not just on availability of resource, but with an eye on what is right to grow and develop people. 
• Help Identify, document and manage delivery risks and issues, ensuring deliver against agreed timelines, quality standards, and service levels
• Ensure the team is delivering against visualisation best practices, as well as internal and external regulatory & compliance standards, such as GDPR, internal audit, and ITIL
• Work with architecture and engineering teams to help shape future roadmap, keeping across industry BI & MI developments and products, to ensure that get the best from current technology and understand what impact new technologies can offer
• Significantly contribute towards the creation, maintenance, and articulation to a team of a clear roadmap of how to consolidate and deprecate legacy solutions, transitioning to self-service solutions, built on top of core data platforms in the Cloud
• Manage a talented team of 5-6 Data Engineers and BI Analysts, to help grow and develop them further
• Responsible for the full lifecycle of the data ingestion from integration, transformation, testing, data quality to monitoring and incident response
• Analyse technology and resource needs to assess the feasibility of projects, and advise on future resourcing needs
• Responsible for the hiring process for the team

Skills: Team Leadership and Development, Resource Management, Risk and Compliance Management, BI & MI Roadmapping, Technology Integration Strategy, Data Lifecycle Management, Project Feasibility Analysis, Recruitment and Hiring.

• Lead team(s) of data analysts that analyze customer data to develop actionable insights to drive customer behavior and operational efficiencies
• Partner with Technology and Data Engineering resources to design, build and implement data platforms in support of analytics, reporting, marketing, operations, etc.
• Lead team(s) and individually conduct root-cause analysis to identify patterns and trends
• Explain data anomalies, develop data visualizations and reporting to drive key messaging and recommendations
• Lead process improvement and project management engagements for both individual teams and cross-organization projects
• Responsible for the design, development, and maintenance of databases, data marts and dashboard tools
• Orchestrates data quality/integrity improvements for critical data elements
• Lead strategic projects related to new product deployment and customer-level aggregation deliverables
• Support Marketing data extracts, and campaign execution including segmentation analysis. 
• Provide observations and business context to deliver meaningful insights to business leads related to campaigns/offers
• Establish best practices for cross-team collaboration and software development processes

Skills: Data Analysis Leadership, Platform Design and Implementation, Root-Cause Analysis, Data Visualization and Reporting, Process Improvement and Project Management, Database Development and Maintenance, Data Quality Management, Strategic Project Leadership.

• Build strong process and constantly recruit to ensure the right mix of top talent is available on teams.
• Leverage processes and frameworks ensure skill growth of team members allowing transparency on career progression for engineers.
• Partner with tech leads to coach and mentor engineers, striving to have each contributor bring best self forward every day.
• Lead the growth and maturation of Hagerty’s data engineering practice.
• Exhibit a strong growth and product mindset.
• Provide clear context and direction on the problems teams have been tasked with solving.
• Craft and maintain an impact-focused technical vision that aligns with the Enterprise Data program vision, and functions as a North Star for maturing the data engineering domain.
• Build collaborative cross-functional relationships with leaders, architects, and technical staff to ensure broad strategic alignment and successful delivery of data solutions.
• Ensure the resiliency of data pipelines through elegant engineering solutions.
• Define best practices for the delivery of the team’s solutions. 
• Partner with architects and tech leads to support the development of robust and scalable data pipelines using Python, SQL, Spark, and data orchestration utilities such as Apache Airflow.

Skills: Talent Recruitment, Skill Development Frameworks, Engineering Mentorship, Data Engineering Leadership, Growth Mindset, Strategic Problem-Solving, Cross-Functional Collaboration, Data Pipeline Resilience.

• Plan and deliver technology and business value to the Client and Accenture by leveraging a deep understanding of value based & transaction-based deals.
• Ensure that the platform requirements are dynamically managed to stay aligned to the business drivers
• Drive or contribute to commercial and contractual discussions with the client & Accenture stakeholders to ensure that the value proposition for the program is clearly defined and articulated
• Define and manage the realization of value delivered from the platform on an ongoing basis including effective reporting to the relevant stakeholders
• Manage client expectations in terms of overall delivery along with Delivery leads on the ground
• Establish methodology and accelerators to reduce initiation efforts from engagement to engagement
• Develop an overarching and compelling sales narrative around the offering
• Become a trusted advisor to help clients, team, and Accenture Leadership stay current on trends, and innovations across areas of expertise
• Harvest and build thought leadership, assets, best practices and contribute to the continuous growth of the company 
• Collaborate with business partners, data scientists and IT teams to define the business requirement and ensure the requirements are met through application.
• Bring deep domain understanding in Commercial operations, Sales & Marketing. 

Skills: Strategic Planning, Platform Alignment, Commercial Negotiations, Value Reporting, Stakeholder Management, Methodology Optimization, Narrative Development, Domain Expertise.

• Deliver data strategy priorities for key data quality engagements in an Agile manner with appropriate documentation of processes, current state analysis, functional requirement specifications & business requirement document and communication throughout the delivery of services.
• Performing tests on large datasets to determine data quality, integrity, and accuracy. 
• Running data queries to identify issues and data exceptions. 
• Determine root cause for data quality errors and make recommendations for long-term solutions.
• Reporting data analysis findings to management to inform business decisions and prioritize information system needs. 
• Propose and document further Data Quality cleansing rules. 
• Evaluating system performance and design, as well as its effect on data quality.
• Keeping abreast of developments and trends in data quality analysis. 
• Adhering to best practices in data analysis and collection.
• Brings good understanding of enterprise approved schema, tools and platforms and can demonstrate them to deliver high quality clean, and linked data across projects.
• Manage agile projects using cloud solutions

Skills: Agile Data Strategy Implementation, Data Quality Testing, Query Execution and Issue Identification, Root Cause Analysis, Business Reporting and Decision Support, Data Cleansing and Documentation, System Performance Evaluation, Cloud Project Management.

• Coach, mentor, and lead a group of highly skilled
• Work collaboratively with business leadership to understand and define success metrics then build appropriate KPI dashboards
• Be responsible and accountable for business intelligence throughout the organization
• Lead plan, design, development, and deployment of analytical environment
• Own projects and manage teams by guiding them in the greater ecosystem. 
• Find new solutions to large, open-ended problems that may be ambiguous and/or lacking clear precedent.
• Manage a team of Data Engineers, and mentor/coach members of the team. 
• Engage in community contributions to improve and sustain culture and operations - making Google a better place to work.
• Lead all aspects of data product, infrastructure, and solution design and development.
• Oversee the integration of multiple teams or work streams.
• Act as the point of contact in areas of expertise, with knowledge in the data infrastructure (e.g., Big Data, Systems Design, Systems Admin, Machine Learning, Networking).

Skills: Leadership and Mentoring, Business Intelligence Management, KPI Dashboard Development, Analytical Environment Design, Innovative Problem Solving, Data Engineering Team Management, Community Engagement, Data Infrastructure Expertise.

• Oversee people leadership for the business unit with a particular focus on stakeholder needs, quality, continuous improvement, and problem-solving
• Sets priorities and assigns tasks to team resources
• Responsible for creating development plans to build on employee strengths
• Manages performance, has authority to hire and terminate employees, and makes compensation recommendations for supervisors and/or individual contributors
• Implements data governance and data integrity for the business unit
• Creates and enforces rules related to data requirements, processes, methodologies, and documentation and ensures development follows best practices
• Creates shared goals with the business unit’s clients and stakeholders on data integrity and proper uses of data
• Continually scan environments for improvements in security, stability, and throughput while managing costs.
• Monitors relevant and valid data sources
• Identifies, communicates, and utilizes data engineering best practices
• Leverages data engineering knowledge to design, maintain, and evolve data services to analytics teams.

Skills: People Leadership, Data Governance, Performance Management, Stakeholder Engagement, Continuous Improvement, Data Integrity Enforcement, Cost Management, Data Engineering Best Practices.

• Direct management of a team of Data/ETL Engineers and Report Developers who work on agile projects
• People development and management
• Can act as Agile Project Manager and hire new people
• Responsible for velocity, quality, and customer satisfaction
• Manage technical projects focused on building data & analytics solutions in Microsoft Azure, design technical solutions to obtain, process, store and provide data products to the business
• Guide and define data engineering approach for technical teams
• Manage deployments of already existing solutions in Microsoft Azure environment
• Suggest architecture improvements
• Work on automation and optimization of internal processes in Azure
• Work with multifunctional and multinational teams within and outside of P&G
• Ensure integrity of existing and new solutions with a focus on operations, reliability, security and scalability

Skills: Team Leadership, Agile Project Management, Microsoft Azure Expertise, Data Engineering, Process Automation, Technical Solution Design, Multinational Collaboration, Solution Integrity and Scalability.

• Responsibility for the design, development, delivery, and maintenance of key data products on GCP that are then used across the business for reporting, analysis, predictive modelling and decisioning
• Provide expertise as the subject matter expert (SME) for data subject areas, owning associated data models, or support the capability and management of tools that are used across the data and digital community
• Ensure that the data products delivered and adequately maintained are of a high quality and accurate
• Manage the team’s utilisation to maximize productivity and ensure resources are appropriately challenged
• Ensure that all products are thoroughly tested and signed off before providing to end customers
• Streamline the development of data products by removing manual activities, complexity and duplication
• Ensure resource capabilities are kept up to date and team members are provided with learning and expansion opportunities
• Manage the team dynamics to ensure cognitive diversity can flourish and is positively encouraged
• Ensure fit-for-purpose documentation is maintained for the data assets and processing to aid control and knowledge sharing
• Uphold and advocate best practice policies and principles for data development and management
• Acts as a bridge between product, analysts, data science and data engineering to promote vision and direction for future projects and business needs.
• Ensures all products have been tested, confirmed, validated, and vetted prior to delivery to stakeholders

Skills: GCP Proficiency, Data Product Design and Delivery, Data Quality Assurance, Team Resource Management, Process Optimization, Documentation Management, Cross-Functional Collaboration, Stakeholder Engagement.

• Lead a team of engineers to build scalable and high-performant data pipelines, using the right software patterns and continuous deployment/integration practices
• Work in one of the data teams, alongside data scientist, product managers and data users
• Collaborate with upstream system architects, developers and data product managers to support and resolve data issues
• Work in a DevOps environment on EPS Data Cloud (AWS) platform
• Implement the tools and processes to handle performance, scale, availability, accuracy and monitoring
• Collaborate in an agile and dynamic environment to lead change and keep them up to date with the latest technologies
• Lead the development of a Data Lake data solution.
• Build detailed knowledge of data sources.
• Build re-usable code and data assets using Software Engineering best practices.
• Coach and mentor a team of 5 developers and engineers and share data knowledge and best practices across the business.
• Ensure Data Governance practices are followed.
• Recruit, retain and motivate a high calibre of technical individuals at all levels.

Skills: Data Pipeline Development, Software Engineering Best Practices, DevOps, AWS Data Management, Agile Collaboration, Data Lake Development, Data Governance, Leadership and Team Building

• Demonstrated experience providing customer-driven solutions, support, or service.
• Advanced knowledge and experience using a variety of programming languages to implement and operate real-time and batch data processing and enable data science and analytics (e.g., Scala, Python, Java, R, C/C++).
• Demonstrated experience developing and managing complex technical projects involving parallel or distributed computing, including Apache Stack (Spark, Storm, Kafka, etc.), and related technologies such as CI/CD automation and micro-service architecture.
• Demonstrated experience working across a broad range of information technology domains, including application, data, infrastructure, and security with specific expertise in design, development, and deployment of data- and analytics-related platforms and tools.
• Demonstrated experience working with or on a Data Science team and familiarity with data mining and machine learning techniques.
• Experience managing and coaching developers
• Expert in SQL and demonstrated the use of JIRA/Workfront/GIT or similar tools to deliver high-quality products
• Knowledge of Salesforce or Microsoft Dynamics
• Knowledge of programming languages, technologies such as JavaScript frameworks, HTML5, CSS, RESTful Services, C++, Spark, Kafka, Redis, etc.
• Professional software and data engineering experience on customer-facing products

Qualifications: BS in Computer Science with 10 Years of Experience

• Previous management or team lead experience
• Proven experience in business intelligence products like data lake, data warehousing and data engineering (ETL/ELT)
• Experience developing data products in Java or Python in the cloud
• Proficient in T-SQL
• Excellent interpersonal and communication skills
• Fluent English speaker
• Affinity with working in an Agile development environment and established e-commerce businesses
• Proven experience in working with high volume websites and e-Commerce b2c retail product development.
• Experience with the Google Cloud Platform 
• Ability to adjust and adapt to changing situations in stride communicating effectively to achieve buy-in and minimizing the downstream effect on performance and morale
• Problem-solving skills

Qualifications: BS in Statistics with 8 Years of Experience

• Experience as a Manager leading a software engineering or data engineering team
• Software engineering experience (Python, Scala, and Java) in a data-focused role
• Experience with dev/data ops to enable the team to move at scale
• Proven track-record of solving complex data processing and storage challenges through scalable, fault-tolerant architecture
• Significant prior experience in designing and building highly scalable and reliable data pipelines using BigData (Airflow, Python, Redshift/Snowflake).
• Software development experience with proficiency in Python, Java, Scala, or another language.
• Prior experience shipping scalable data solutions in the cloud (AWS, Azure, GCP) and database technologies such as Snowflake, Redshift, SQL/NoSQL and or columnar databases
• Can learn new technologies quickly
• Experience optimizing Data Pipelines and Data delivery
• Strong communication skills with the ability to communicate details about the technical practices in software engineering in a way that makes sense and resonates with other business teams
• Experience with building, maintaining, and scaling PetaByte scale Data Pipelines
• Experience with workflow scheduling tools like Airflow

Qualifications: BS in Information Systems with 5 Years of Experience

• Experience designing data models/data warehouses, using database management systems (SQL, NoSQL), and data processing using traditional/distributed systems (Hadoop, Spark, Dataflow).
• People management experience.
• Experience with programming languages (e.g., Java, C/C++, Python, etc.).
• Experience with large-scale distributed data processing and with Unix or GNU/Linux systems.
• Experience designing data models and data warehouses.
• Experience with non-relational data storage systems (e.g., NoSQL and distributed database management systems).
• Experience writing and maintaining ETLs which operate on a variety of structured and unstructured sources.
• Excellent communication, organizational, and analytical skills.
• Experience in Data Engineering with recent hands-on experience managing Data Engineers
• Knowledge of technologies/languages in Spark, Hadoop, Python, Scala, AWS, Athena, Hive, S3, Docker, etc
• Demonstrate advanced knowledge of ETL development, Data Warehousing, Big Data systems, large scale transformations, and data modeling.
• Has a strong problem-solving and analytical approach

Qualifications: BS in Software Engineering with 12 Years of Experience

• Work experience in the Data Engineering field
• Experience in leading and managing engineering teams
• Experience working with Hadoop and Big Data processing frameworks (Spark, Hive, Nifi, Spark-Streaming, Flink, etc.)
• Experience building scalable, real-time, and high-performance cloud data lake solutions
• Solid experience with relational SQL and programming languages such as Python, Scala, or Java
• Experience with source control tools such as GitHub and related CI/CD processes
• Experience working with Big Data streaming services such as Kinesis, Kafka, etc.
• Experience working with NoSQL data stores such as HBase, DynamoDB, etc.
• Experience provisioning RESTful APIs to enable real-time data consumption
• Experience working in AWS environment primarily EMR, S3, Kinesis, Redshift, Athena, etc
• Experience with data warehouses/RDBMS like Snowflake & Teradata
• Hands-on experience with a track record of analysis, design, Prototype, develop, deploy Data and BI solutions in complex corporate IT platforms

Qualifications: BS in Data Science with 11 Years of Experience

• Management experience leading a team of data engineers
• Adept at prioritizing multiple issues in a high pressure environment
• Ability to conduct performance analysis and fix large-scale distributed systems
• Experience in high-level programming languages such as Java, Scala, or Python.
• Proficiency with DataWarehouse and database platforms like Teradata, Oracle, Snowflake, BigQuery and SQL
• Proficiency in data processing using technologies like Pl/SQL, BTEQ, Spark Streaming, Spark SQL, or Map/Reduce.
• Expertise in Hadoop-related technologies such as HDFS, Azkaban, Oozie, Impala, Hive, and Pig.
• Expertise in developing big data pipelines using technologies like Kafka, Flume, or Storm.
• Knowledge of foundation infrastructure requirements such as Networking, Storage, and Hardware Optimization with Hands-on experience with any cloud Infrastructure (AWS, Azure, Google Cloud)
• Experience with large-scale data warehousing, mining, or analytic systems.
• Aptitude to independently learn new technologies.
• Have a solid grasp of advanced data warehouse concepts (Factless Fact tables, Temporal \ BI-Temporal models, etc.)
• Ability to work with analysts to gather requirements and translate them into data engineering tasks.

Qualifications: BS in Computer Science with 15 Years of Experience

• Excellent SQL skills and people skills 
• Experience in data extraction, manipulation and visualisation tools, e.g. Snowflake, Tableau, Periscope, and Looker
• Experience as a Business Analyst in a contact centre environment
• Have experience working within a contact centre environment (onshore/offshore)
• Strong analytical mindset and critical thinking ability
• Has a deep desire to solve real-world problems and sees the beauty of data, and structure and how important these are to understanding a problem and identifying effective solutions.
• Has solid Excel and modelling skills i.e., pivot tables and INDEX MATCH
• Working knowledge of MS PowerPoint and MS Word
• Working knowledge of MS Sharepoint and MS PowerAutomate
• Must be able to work cross-functionally.
• Enterprise development experience using Java, Node, Python

Qualifications: MS in Data Science with 3 Years of Experience

• Experience scaling and managing 5+ person teams.
• Communication and leadership experience, with experience initiating and driving projects.
• Experience analyzing data to identify deliverables, gaps, and inconsistencies.
• Data architecture experience.
• Experience in SQL or similar languages.
• Development experience in at least one object-oriented language (Python, Perl, Java, etc.).
• Experience in custom or structured (Informatica/Ab Initio/Talend/Pentaho, etc.) ETL design, implementation, and maintenance.
• Experience working with a MapReduce or an MPP system.
• Experience leading data driven discussions & designing scalable data platforms for analytics.
• Experience with enterprise data solutions.
• Experience with data sets, Hive, and data visualization tools.

Qualifications: BS in Software Engineering with 4 Years of Experience

• Understanding of development methodology and actual experience writing functional and technical design specifications.
• Excellent verbal and written communication skills, in person, by telephone, and with large teams.
• Strong prior technical, development background in either data Services or Engineering
• Demonstrated experience resolving complex data integration problems
• Strong mastery of Power BI
• Strong mastery of SQL, Data warehousing, Table provisioning, Query authoring, etc.
• Strong mastery of Python and/or Scala programming
• Strong mastery of SDLC, Agile, Waterfall software development principles
• Strong mastery of Azure Databricks (SQL, Spark, ML)
• Working knowledge of JIRA issue management and development workflows
• Working knowledge of MS Excel and its built-in computing and statistical capabilities

Qualifications: BS in Information Systems with 7 Years of Experience

• Experience in Databricks, Data/Delta lake, Oracle, SQL Server, or AWS Redshift-type relational databases.
• Experience in ETL (Data extraction, data transformation and data load processes)
• Working experience in data integration and pipeline development.
• Excellent experience in Databricks and Apache Spark.
• Data lake and Delta lake experience with AWS Glue and Athena.
• Experience with AWS Cloud on data integration with Apache Spark, Glue, Kafka, Elastic Search, Lambda, S3, Redshift, RDS, MongoDB/DynamoDB ecosystems.
• Strong real-life experience in python development especially in pySpark in AWS Cloud environment
• Experience in Python and common Python libraries.
• Strong analytical experience with databases in writing complex queries, query optimization, debugging, user defined functions, views, indexes etc.
• Strong experience with source control systems such as Git and Jenkins build and continuous integration tools.
• Highly self-driven, execution-focused

Qualifications: BA in Statistics with 7 Years of Experience