Job Summary: 

• Take ownership of the design, development, maintenance and testing strategy of DS applications
• Collaborate with business leads across Sportsbook and Engineering to define milestones and deliverables for new DS products or enhancements to existing products
• Contribute to the architecture and design of DS projects and strategic initiatives, with a specific focus on quality, stability, and efficiency
• Mentor and lead design and knowledge transfer sessions, ensuring that other DS engineers deliver high-quality work
• Lead portfolio of multiple data projects and work closely with business and IT functions to deliver data projects in a timely and efficient manner
• Lead development of provisioning data pipes for reporting and data science
• Map the base data elements that need to be transformed and provisioned
• Work with the business to get an understanding of their data requirements
• Help the Business improve processes and help the business make data-driven decisions

Skills on Resume: 

• Data Architecture (Hard Skills)
• Data Pipelines (Hard Skills)
• System Design (Hard Skills)
• Project Leadership (Soft Skills)
• Stakeholder Collaboration (Soft Skills)
• Requirements Analysis (Hard Skills)
• Technical Mentoring (Soft Skills)
• Data Strategy (Hard Skills)

Job Summary: 

• Accountable for providing a quality service or product to customers and stakeholders, using skills/experience built through significant practical experience or training
• Work across multiple disciplines across the Investment Data Platform and opportunities to connect and improve working practices
• Works within established frameworks and procedures, with the freedom to interpret them to solve a range of problems
• Delivers outputs that are clearly defined, using discretion over how to achieve them
• Makes suggestions for improvements to the work of the team, based on previous experience and knowledge of similar situations
• Develop scalable analytical solutions for investment teams across multiple asset classes in an agile development environment
• Lead the development of solutions end-to-end and see it through until it reaches the end customer
• Sometimes this will encompass requirements gathering, data modelling, data integration, and software engineering
• Build various (micro) apps/services on established development frameworks to further aid the solutions rolling out across the work floor
• Build and maintain strong relationships with all key stakeholders in the Front Office, Sustainability-focused teams, Transformation and Innovation or the engineering community

Skills on Resume: 

• Service Quality (Soft Skills)
• Analytical Solutions (Hard Skills)
• Agile Development (Hard Skills)
• End-to-End Delivery (Hard Skills)
• Data Modelling (Hard Skills)
• Data Integration (Hard Skills)
• Microservices Development (Hard Skills)
• Stakeholder Management (Soft Skills)

Job Summary: 

• Develop, construct, test and maintain the AdScience analytics platform
• Design, implement and enhance ETL (extract, transform and load) processes
• Create reports/dashboards using visualization tools
• Assemble, transform, and persist large and complex data sets that meet functional and non-functional business requirements
• Build and optimize data pipelines, architectures, and data sets
• Builds moderate-level complexity data interfaces, connecting to both internal and external sources
• Participates in the design of data architecture standards
• Designs and implements database logical and physical models
• Provide development and production support to troubleshoot all data interfaces and data model-related issues
• Implement systems for tracking data quality and consistency
• Make data discoverable and accessible to business users
• Successfully communicate and work with department leadership, external contacts, and cross-functional teams to perform responsibilities
• Maintain confidentiality of personal information

Skills on Resume: 

• Data Engineering (Hard Skills)
• ETL Development (Hard Skills)
• Data Pipelines (Hard Skills)
• Data Architecture (Hard Skills)
• Database Modeling (Hard Skills)
• Data Visualization (Hard Skills)
• Data Quality (Hard Skills)
• Cross-Functional Communication (Soft Skills)

Job Summary: 

• Develop data integration and ETL/ELT components using the DataOps framework
• Develop the data pipeline from ingestion through to consumption
• Work closely with the Data Architect to turn conceptual data models into logical and physical models using best practices to ensure high data quality and reduced redundancy
• Help to develop test scenarios and automated test cases in collaboration with the test team, accountable for development quality
• Lead, coach and collaborate with a small diverse team 
• Establish and evolve data capabilities and help to embed best practices
• Design, build and operate a cloud native real-time data platform using modern event-driven architectures
• Bring a high level of motivation and enthusiasm to the team
• Configure and customize the chosen ETL tool for client installations
• Optimally leverage the ETL tool components for developing efficient solutions for data management, conversion, migration, and integration
• Develop overall design and determine division of labor across various architectural components (for example, ETL tool vs. database)
• Deploy and customize Standard Architecture components
• Support the development of task plans, including schedule and effort estimation, under the guidance of an ETL architect

Skills on Resume: 

• DataOps Framework (Hard Skills)
• ETL/ELT Development (Hard Skills)
• Data Pipeline Design (Hard Skills)
• Cloud Data Platforms (Hard Skills)
• Event Driven Architecture (Hard Skills)
• Data Modeling (Hard Skills)
• Technical Leadership (Soft Skills)
• Team Collaboration (Soft Skills)

Job Summary: 

• Work with business teams to understand the problem statement, identify the different stakeholders and systems
• Ability to work with different teams/groups within/outside the organization and supplier partners to ensure smooth end-to-end delivery of the projects
• Identify, design, develop and test database architectures and large-scale processing solutions
• Guiding and leading the project delivery team and hands-on development work
• Recommend and implement ways to improve data reliability, efficiency and quality
• Propose tools and languages to marry data sources together to hunt down opportunities provided by the data acquisition
• Research to answer business questions around data
• Develop data set processes for data modeling, mining and production and leverage large volumes of data
• Automate work to build pipelines to harness data from their source to be used in advanced analytic techniques
• Managing vendor resources and deliveries

Skills on Resume: 

• Stakeholder Analysis (Soft Skills)
• Cross-Functional Delivery (Soft Skills)
• Database Architecture (Hard Skills)
• Data Reliability (Hard Skills)
• Pipeline Automation (Hard Skills)
• Advanced Analytics (Hard Skills)
• Data Research (Hard Skills)
• Vendor Management (Soft Skills)

Job Summary: 

• Leads planning sessions with customers to improve business processes and prioritize investments in process, people, services, and infrastructure
• Accountable for the development of guidelines and standards to be utilized in data architecture and data integration including developing technical skill sets on the team and leading implementation plans
• Accountable for maintenance and upgrade planning over data architecture platform, data integration platforms, and the data warehouse
• Lead the team to develop, communicate, and drive a technical vision in partnership with the Enterprise Data Architect that is easily understood by all levels of management
• Makes recommendations on work priorities that lie outside project deliverables
• Lead activities to provide customer support and resolution of incidents for all data platforms
• Provides technical guidance, leadership and coaching to team members, including sharing business acumen
• Mentor peers and identify/develop training plans and strategies to maintain technical currency
• Influences enterprise information systems opportunities that align with corporate strategy and performance
• Create and present a polished executable plan with risk factors identified
• Serve as the technical lead on large, complex IT projects

Skills on Resume: 

• Strategic Planning (Soft Skills)
• Data Architecture (Hard Skills)
• Platform Governance (Hard Skills)
• Technical Leadership (Soft Skills)
• Incident Management (Hard Skills)
• Enterprise Influence (Soft Skills)
• Risk Management (Soft Skills)
• Complex Delivery (Hard Skills)

Job Summary: 

• Develop streaming data pipelines from IoT/Timeseries data
• Develop data integration and ETL components by coding utilities, responding to user questions, and resolving problems
• Maintain the overall performance of components involved in Data Integration through ETL tools like Informatica
• Elicit business requirements from key stakeholders and business analysts by using interviews, document analysis, requirements workshops, competitive product analysis, task and workflow analysis
• Work with the Data Architect to turn conceptual data models into logical and physical models using best practices to ensure high data quality and reduced redundancy
• Implement and document data architectures and data models consistent with business and technical requirements
• Create, support and optimise data models (CDM, LDM and PDM) as well as find creative solutions for a variety of challenges facing growing data requirements
• Help to develop test scenarios and test cases in collaboration with the central test team, along with acceptance criteria
• Identify and drive opportunities to reuse data models in new environments
• Communicate with both technical and non-technical staff, stakeholders, end-users, and vendors
• Work with enterprise architects, solution architects, data architects, data scientists, and business SMEs and assist them with any data questions
• Provide support in assessing data quality through a data validation exercise

Skills on Resume: 

• Streaming Pipelines (Hard Skills)
• ETL Development (Hard Skills)
• Data Integration (Hard Skills)
• Data Modeling (Hard Skills)
• Data Architecture (Hard Skills)
• Requirements Elicitation (Soft Skills)
• Stakeholder Communication (Soft Skills)
• Data Quality (Hard Skills)

Job Summary: 

• Implement and optimize a data processing pipeline for terabytes of data
• Design and build a data warehouse as well as real-time data reporting systems
• Promote and nurture good team practices such as unit testing, code reviews, build/test automation, etc.
• Proactively mentor and guide application developers to improve their quality and simplicity in design and code
• Design, build and use tools to understand product platform behavior and performance
• Design and conduct experiments to test concepts, technologies, and algorithms
• Implement analytics tools to maximize the value of collected data
• Implement data tests in the data quality framework to ensure data is clean and accurate
• Adhere to security policies and guidelines to ensure data is protected and safe
• Embrace and assist in evolving Agile (Scrum) team processes and developer role responsibilities
• Own the discovery, delivery, evolution, and maintenance of the team’s complex data projects

Skills on Resume: 

• Data Pipelines (Hard Skills)
• Data Warehousing (Hard Skills)
• Real Time Reporting (Hard Skills)
• Code Quality (Hard Skills)
• Technical Mentoring (Soft Skills)
• Experiment Design (Hard Skills)
• Data Analytics (Hard Skills)
• Agile Practices (Soft Skills)

Job Summary: 

• Implementing the Retail Banking Capital, Finance and Stress Testing Models in Java and Python-based technologies
• Driving efficiencies in implementation
• Following SDLC standards for build and delivery
• Identifying and resolving production and application development problems
• Adhering to Agile methodology, ensure requirements documentation complies with Agile and audit standards
• Coordinating change across diverse teams from a variety of disciplines
• Implementing the models developed by Quantitative Analytics in the Model Execution Framework 
• Implementing the orchestration of the execution of the models

Skills on Resume: 

• Model Implementation (Hard Skills)
• Java Development (Hard Skills)
• Python Development (Hard Skills)
• SDLC Compliance (Hard Skills)
• Production Support (Hard Skills)
• Agile Delivery (Soft Skills)
• Cross-Team Coordination (Soft Skills)
• Workflow Orchestration (Hard Skills)

Job Summary: 

• Deliver a wide range of data enhancements and solutions across the business
• Hands-on leadership of the Data Engineering team
• Lead the support and maintenance of the firm's data infrastructure/architecture
• Best practice-led design and delivery of data solutions
• Identify and deliver process improvements/enhancements
• Spearhead the firm's journey towards automated testing and deployment
• Take ownership of building data solutions to provide actionable insights into key business metrics
• Collaborate and serve as the technical lead of the data team (‘squad’) to design scalable processes
• Work with product owners, product managers and lead squad to implement high-quality, production-grade data pipelines and ETL processes
• Work with the squad to design, build, and deliver innovative applications with urgency and speed
• Bring operational excellence with a focus on performance analysis, optimization, and tuning

Skills on Resume: 

• Data Engineering (Hard Skills)
• Technical Leadership (Soft Skills)
• Data Architecture (Hard Skills)
• Process Improvement (Soft Skills)
• Automated Deployment (Hard Skills)
• Scalable Design (Hard Skills)
• ETL Pipelines (Hard Skills)
• Performance Optimization (Hard Skills)

Job Summary: 

• Tech lead responsibility, along with being a top-class developer
• Work with product managers to understand customer requirements and design and deliver cloud SaaS services
• Perform the role of data scientist within the team
• Work with functional leads to understand their data requirements
• Design and deliver data pipelines to scale to billions of events
• Collaborate with operations to establish KPI for different services and own end-to-end delivery and lifecycle management
• Establish core data management principles and best practices
• Lead initiatives and projects across multiple geos
• Provide technical leadership and mentoring to team members

Skills on Resume: 

• Technical Leadership (Soft Skills)
• Cloud SaaS Design (Hard Skills)
• Data Science (Hard Skills)
• Requirements Analysis (Hard Skills)
• Scalable Pipelines (Hard Skills)
• KPI Management (Hard Skills)
• Data Governance (Hard Skills)
• Global Collaboration (Soft Skills)

Job Summary: 

• Architect and build Beacon’s cloud-native data infrastructure and DevOps practices
• Hands-on development and coding of data pipelines and deployments
• Expand and manage the Beacon data platform
• Making the data available to all parts of the business and customers
• Design, implement, and maintain automated tools for Beacon’s cloud environment, including testing (ie, CI/CD), monitoring and alerting frameworks
• Designing and developing data pipelines
• Managing the team doing code reviews
• Ensuring the candidates are adhering to best practices 
• Developing the cloud infrastructure on GCP (creative thinking and architecture design)

Skills on Resume: 

• Cloud Architecture (Hard Skills)
• Data Pipelines (Hard Skills)
• DevOps Practices (Hard Skills)
• CI/CD Automation (Hard Skills)
• GCP Infrastructure (Hard Skills)
• Platform Scalability (Hard Skills)
• Code Review (Soft Skills)
• Technical Leadership (Soft Skills)

Job Summary: 

• Analyze and improve cloud-based data architecture
• Design and develop software using cutting-edge technologies, consisting of data pipelines, ETL, big data, machine learning and cloud-based development methodologies
• Key role in the development team to build high-quality, high-performance, scalable code to ingest data from various financial data vendors
• Produce technical design documents and conduct technical walkthroughs
• Collaborate effectively with technical and non-technical stakeholders
• Respond to and resolve production issues
• Responsible for implementing best practices, data standards and reporting tools
• Responsible for general ETL development and implementing new solutions
• Help modernize hybrid technology solutions, including the opportunity to work on modern warehousing and integration technologies

Skills on Resume: 

• Cloud Data Architecture (Hard Skills)
• ETL Development (Hard Skills)
• Scalable Software (Hard Skills)
• Big Data Processing (Hard Skills)
• Technical Documentation (Hard Skills)
• Stakeholder Collaboration (Soft Skills)
• Production Support (Hard Skills)
• Data Standards (Hard Skills)

Job Summary: 

• Develop new features and enhance existing data pipelines
• Contribute to solution design and technical design for new features
• Support data pipeline workload in the production environment
• Monitor job execution, triage and troubleshoot job failures and other issues
• Make code changes to fix production failures and deploy code in production
• Report operations status to all stakeholders at regular cadence
• Identify opportunities to enhance, streamline, and improve the codebase and work with Dev leads to make that happen
• Monitor infrastructure proactively and identify opportunities to improve operational efficiency, job execution performance and overall cost

Skills on Resume: 

• Data Pipeline Development (Hard Skills)
• Technical Design (Hard Skills)
• Production Support (Hard Skills)
• Job Monitoring (Hard Skills)
• Troubleshooting (Hard Skills)
• Operational Reporting (Soft Skills)
• Code Optimization (Hard Skills)
• Cost Optimization (Hard Skills)

Job Summary: 

• Design, build, integrate, and maintain services that are critical to Under Armour’s data foundation
• Mentor fellow Data Engineers on the Data Platform team, as well as cross-functional teammates from organizations such as data analytics, data science, and digital marketing
• Work across teams up and down the data technology and enablement stacks to understand how to improve or expand data products and services
• Contribute to the mission of the Data Platform today and build the vision for its future
• Analyze and improve the efficiency, scalability, and stability of data collection, storage, and retrieval processes for core systems
• Create and manage platform-specific APIs
• Create new data processing systems to support Data Scientists and Research Analysts
• Ultimately, build robust, high-volume production software

Skills on Resume: 

• Data Platform Engineering (Hard Skills)
• Service Integration (Hard Skills)
• Technical Mentoring (Soft Skills)
• Cross-Team Collaboration (Soft Skills)
• Scalable Systems (Hard Skills)
• API Development (Hard Skills)
• Data Processing Systems (Hard Skills)
• Production Software (Hard Skills)

Job Summary: 

• Work closely with the Product Manager, Business Analyst and Architect to understand business and functional requirements, strategy and approach, and lead a team to come up with a solution design
• Contribute with hands-on development, implementation, testing, maintenance, and support of data integrations for the Vehicle MDM team
• Design, build and test highly scalable data pipelines with monitoring and logging best practices
• Conduct RCA (Root Cause Analysis) for system applications
• Design, develop and implement MDM Reltio Security Roles, MDM UI functionality, and Match and Merge Rules for complex entity relationships through Reltio configuration
• Maintain and performance-tune the Reltio configuration codebase
• Define, develop and implement business process workflows through Reltio UI for maintenance of RDM data
• Collaborate with several Product and Technology teams to lead system integration testing, problem-solving and troubleshooting
• Mentor junior and mid-level Data Engineers in design, problem-solving and troubleshooting

Skills on Resume: 

• Solution Design (Hard Skills)
• Data Integration (Hard Skills)
• Scalable Pipelines (Hard Skills)
• Reltio Configuration (Hard Skills)
• MDM Security (Hard Skills)
• Performance Tuning (Hard Skills)
• System Integration (Hard Skills)
• Team Mentoring (Soft Skills)

Job Summary: 

• Building data and analytic tools, or other analytic capabilities for business analysts and data scientists, particularly related to consumer and marketplace insights, supply chain and manufacturing data
• Performing data engineering, data profiling, and/or querying on large, complex data sets to meet functional and non-functional business requirements
• Communicating complex technical information to business customers and project teams in an effective and concise manner
• Participating as a hands-on technical resource or leading technical contractors in IT project development
• Performing design and code review on outsourced ETL (extract, transform, and load) activities
• Assessing technical infrastructure and processes
• Identifying risks and recommending solutions
• Coordinating with multi-functional resources to deliver end-to-end solutions

Skills on Resume: 

• Data Engineering (Hard Skills)
• Analytics Tools (Hard Skills)
• Data Profiling (Hard Skills)
• Large Scale Querying (Hard Skills)
• Technical Communication (Soft Skills)
• Code Review (Hard Skills)
• Risk Assessment (Soft Skills)
• Cross-Functional Coordination (Soft Skills)

Job Summary: 

• Run and manage a world-class team of data engineering talent
• Recruit and train a team of data engineers to scale the offering
• Identify the data sources to curate based on a defined set of target attributes
• Establish the architecture for curating data from the web and 3rd party sources into a handful of data products for key business entities (e.g., companies, people, parts)
• Develop the tooling required to execute on the defined architecture
• Establish a high standard of data quality and freshness, consistent with overall positioning in the market
• Collaborate with the ML team, raising the bar on ML capabilities across the board
• Integrate commercial datasets into the product framework for enrichment

Skills on Resume: 

• Team Leadership (Soft Skills)
• Talent Development (Soft Skills)
• Data Sourcing (Hard Skills)
• Data Architecture (Hard Skills)
• Tooling Development (Hard Skills)
• Data Quality (Hard Skills)
• ML Collaboration (Soft Skills)
• Data Enrichment (Hard Skills)

Job Summary: 

• Design, build, and support data pipelines to facilitate BI and analytics solutions among the team (e.g., ETL)
• Support establishing a self-service BI data environment including data sourcing, modeling and distribution for consumption by citizen BI developers
• Accountable for ensuring data within the store meets quality and security requirements
• Build consensus and trust with partnered organizations on future state patterns
• Drive the sharing of standards on the team and the greater community
• Coaching, mentoring, and articles around core methodologies and processes
• Build reports/dashboards for consumption within the team using BI tooling, such as Tableau or Power BI
• Collecting data systematically and considering a broad range of issues or factors to promote the sustainability of the dataset
• Embrace continuous learning, curiosity, experimentation, and ambiguity

Skills on Resume: 

• Data Pipelines (Hard Skills)
• ETL Development (Hard Skills)
• Self-Service BI (Hard Skills)
• Data Quality (Hard Skills)
• Data Security (Hard Skills)
• BI Reporting (Hard Skills)
• Technical Mentoring (Soft Skills)
• Continuous Learning (Soft Skills)

Job Summary: 

• Lead a team of data engineers
• Use an analytical, data-driven approach to drive a deep understanding of business
• Build data pipelines and data models that will empower engineers and analysts to make data-driven decisions
• Build data models to deliver insightful analytics
• Deliver the highest standard in data integrity
• Analyze and project sales, subscribers and engagement data
• Work closely with analytics teams to develop comprehensive analytical reports to enable data-driven decisions to increase engagement and conversions of target customer segments
• Understanding the PI Framework and recognising opportunities for improvement
• Delivery of process improvements in support of the increasing departmental responsibilities
• Monitoring and improving data standards within the department
• Creating a suite of tools and metrics in support of the departmental transformation
• Managing own throughput and that of the team

Skills on Resume: 

• Team Leadership (Soft Skills)
• Data Driven Analysis (Hard Skills)
• Data Pipelines (Hard Skills)
• Data Modeling (Hard Skills)
• Data Integrity (Hard Skills)
• Sales Analytics (Hard Skills)
• Process Improvement (Soft Skills)
• Performance Management (Soft Skills)