• Provision, configure and maintain AWS cloud infrastructure defined as code using CDK (cloud deployment kit) or CloudFormation.
• Troubleshoot problems across a wide array of services and functional areas.
• Monitor big data and advanced analytics use-cases that are running in a productive cloud environment, including incident management
• Enhance and maintain a proactive ETL pipeline monitoring framework
• Produce, maintain and optimize code based on clear specifications
• Integrate and continuously improve specific framework components
• Coordinate the operational work streams with the cloud infrastructure service provider
• Develop ETL data pipelines and data connectors
• Data quality check implementations and deliveries
• Working closely with Data Engineers and Scientists within a data-dedicated Team

Skills: AWS Infrastructure Provisioning, Problem Troubleshooting, Cloud Monitoring, ETL Pipeline Monitoring, Code Optimization, Framework Integration, Operational Coordination, Data Pipeline Development

• Identify needs and opportunities for improved processes based on data coming from connected machines
• Collaborate with service, marketing and finance in order to create new business value, based on data from connected machines
• Analyze historical machine data in order to learn and extract insights on equipment
• Learn about and outline the potential of descriptive, diagnostic, predictive and prescriptive models and machine-learning algorithms. 
• Ensure information is presented in the best possible way using the latest data visualization techniques and tools. 
• Build solutions/use cases based on data of connected machines that bring business value in daily operations
• Participate in Design and architectural discussions.
• Work collaboratively with the team to gather and define the requirements.
• Convert the requirements into business logic and deploy it on AWS using a suitable service.
• Build and maintain operational tools for deployment, monitoring, and analysis of AWS infrastructure and systems.

Skills: Process Improvement, Cross-Functional Collaboration, Data Analysis, Model Development, Data Visualization, Business Solutions, Requirement Gathering, AWS Deployment

• Interaction with business users and customers to understand the problems and provide help in fixing data pipeline-related issues.
• Develop and maintain Python scripts in Airflow
• Working with the development team, technical leads, business analysts, coordinating with management and understanding the end user expectations to scale the platform/hadoop data pipeline framework.
• Collaborate with various stakeholders across business, data science, and engineering teams to accomplish projects, identifying and implementing efficiencies along the way.
• Serve as an expert for internal discussions and meetings, becoming one of the go-to persons for data pipeline platform-related tasks/issues.
• Communicate effectively (written and spoken) and work with the multi-location development teams and self-manage own work
• Collaborate with team members to innovate and scale the existing platform to improve better developer experience
• Participate in the design, development, and deployment of Data Warehouse data models, including DB systems and Analytics Data.
• Participate in the design, development, and deployment of data pipelines crossing internal subsystems to deliver Business/Data team for building full OMNI viewports on customers, products, transactions, demand forecast etc.
• Collaborate with business users to ensure high-quality data sets are delivered
• Troubleshoot operational escalations and resolve business partner issues in a timely manner with strong collaboration and care for business priorities
• Document existing and new work performed

Skills: User Interaction, Python Development, Pipeline Scaling, Stakeholder Collaboration, Platform Expertise, Data Modeling, Pipeline Deployment, Issue Resolution

• Create and maintain optimal data pipeline architecture
• Initiate new data collection streams with guidance from the product team to determine parameters or processes to monitor
• Develop, construct, test, and maintain the data architecture.
• Responsible for the assurance, if the architecture will support the requirements of the business and discovering opportunities for data acquisition.
• Developing data set processes for data modelling, mining and production is another of the main tasks.
• Implement secure and scalable API endpoints to make the computed data available.
• Recommend ways to improve data reliability, efficiency and quality and collaborate with data analysts/scientists and the BI Team to implement new ELT pipelines.
• Implementing new solutions based on fast and insightful combinations of data
• Scaling solutions to terabytes of data and applying cutting-edge machine learning to it
• Creating neural language models for chemistry, designing large-scale graph algorithms and machine learning paradigms to bring human experts in the loop (active and reinforcement learning)

Skills: Pipeline Architecture, Data Collection, Architecture Development, Data Process Design, API Implementation, Data Quality, Scalable Solutions, Machine Learning

• Build and enhance the software stack for modelling and data analytics
• Incorporate relevant data-related algorithms in the products to solve business problems and improve them over time
• Automate repetitive data modelling and analytics tasks
• Keep up to date with available relevant technologies to solve business problems
• Closely work with analytics users to understand needs & provide recommendations/solutions
• Help define/share best practices for the business users and enforce/monitor that best practices are being incorporated for better efficiency (speed to market & system performance)
• Share daily/weekly progress made by the team
• Work with senior stakeholders & drive the discussions independently
• Mentor and lead a team of software developers on analytics-related product development practices

Skills: Software Development, Algorithm Integration, Task Automation, Technology Research, User Collaboration, Best Practices, Progress Reporting, Team Leadership

• Supporting the data infrastructure that drives analytical insights, data intelligence, and dashboards.
• Writing scripts (Python, Java, SQL) and creating data pipelines for storing data within Amazon Web Services (AWS) infrastructure (Redshift, S3, S2).
• Design and build an efficient ETL / ELT infrastructure for both structured and unstructured data sources
• Monitor and maintain existing data pipelines and infrastructure currently in production
• Help drive optimization, testing, and tooling to continuously improve data quality
• Research and implement multiple API connections for data extractions
• Complies with Network and Urban One’s mandatory trainings and adheres to related course deadlines
• Identify, design, and implement internal process improvements including automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
• Apply statistical methodology to complex data, distill large, complex data sets into technical presentations to management
• Interact with other functional and international teams to ensure alignment of data collection, analysis, and reporting amongst the three facilities
• Propose, lead, and participate in data-driven projects utilizing DMAIC and DMADV principles.

Skills: Data Infrastructure, Pipeline Development, ETL Design, Pipeline Maintenance, Data Optimization, API Integration, Process Improvement, Statistical Analysis

• Construct real-time visual KPI dashboards tailored to each department to provide a snapshot of status.
• Collect, collate, cleanse, synthesise and interpret data to give meaningful & actionable insights to inform decisions
• Produce standardised static reports for customer communication over a given timeframe.
• Re-engineer manual data flows to enable scaling and repeatable use
• Scope requirements for any given development project in the form of a report and/or flowchart/map detailing tasks, data flow, interactions with other systems, inputs and outputs through gaining a comprehensive understanding of the tasks, current procedures and expected outcomes for the new or improved application.
• Segment larger projects into agreed sections to enable implementation of primary functionality to end users within an acceptable timeframe.
• Identify and demonstrate any existing applications that could meet the needs of the project immediately or with minimal modification.
• Facilitate development projects by liaising between developers and end users, breaking down any technical jargon for both parties and clarifying any confusion or areas of misunderstanding.
• Ensure agreed timescales are based on a full understanding of the scope and available resources - slippages to be escalated to relevant parties with the relevant reasons captured and understood.
• Plan, design, manage and execute testing of new reporting functions or added functionality ensuring any issues are resolved prior to end user testing.
• Train and roll out new or improved applications to key users and provide appropriate training documentation.
• Ensure risks are adequately understood and documented. 

Skills: KPI Dashboards, Data Interpretation, Report Production, Data Automation, Requirement Scoping, Project Segmentation, User Facilitation, Function Testing

• Work closely with business teams to develop working software that delivers the desired business outcome
• Support the APAC Digital Marketing data agenda through the application of appropriate technologies, to gain insights about customers' engagement with Schroders' digital channels
• Develop and document the provisioning and management of data pipelines
• Explore ways to improve technology processes to progress the Marketing Analytics function across a broad range of areas such as cost savings, security, ease of use, & reliability
• Play a key role in familiarising the extended team with data engineering tools and best practices
• Capture and analyse technology requirements that can be quickly delivered using the Agile delivery processes and tooling
• Discover and playback innovative functionality and potential new ways to realise additional business benefits
• Maintain an understanding of industry trends and how new technologies can be leveraged to meet business objectives
• Work closely with the Systems Architect to ensure that standards are adhered to and any necessary architectural or technical debt is recorded with a realistic plan to remediate
• Engage actively in Agile planning including story refinement, demos and retrospectives
• Support other team members to improve software development skills
• Assist with the role of Scrum Master to do so

Skills: Business Collaboration, Marketing Analytics, Pipeline Management, Process Improvement, Team Enablement, Agile Delivery, Technology Innovation, Scrum Support

• Work with Business Analysts and Business Application Owners to translate business requirements and use cases into technical and data requirements
• Identify source system tables and fields that need to be brought into Celonis
• Find the best method of loading source system data for each process implemented within Celonis
• Collaborate with IT system experts to ensure the IT systems are set up correctly to gather all relevant information and support the most effective data structures
• Build the Celonis data model for each process
• Collaborate with relevant business experts to validate the data within Celonis
• Monitor and optimize the performance of all data queries to ensure ideal response times
• Document all technical and data requirements and all extract, transform, load (ETL) work
• Provide ongoing support for any data-related issues
• Assist with user enablement and the establishment of the Celonis governance model

Skills: Requirement Translation, Data Sourcing, Data Loading, System Collaboration, Model Building, Data Validation, Query Optimization, Technical Documentation

• Develop automated data ingestion and wrangling algorithms to process, wrangle and link data from a diverse set of sources
• Create and maintain optimal data pipelines for Data Science and advanced analytics initiatives
• Build the infrastructure required for optimal extraction, transformation and loading of data from a wide variety of data sources using SQL and big data technologies.
• Work with Data Scientists in the development of machine learning apps on the Cloud Platform
• Work with stakeholders including external vendors, IT, tech platform and IT operations teams, to assist with data-related technical issues and support data infrastructure needs
• Identify ways to improve data reliability, efficiency and quality
• Work with external vendors and data providers to develop data assets in on-premises Data Warehouse and on the Cloud platform
• Work with data and analytics experts to strive for greater functionality in data systems.
• Identify automation opportunities and optimise data delivery and reporting
• Responsible for the day-to-day management of data platforms

Skills: Data Ingestion, Pipeline Development, Infrastructure Building, Cloud Collaboration, Technical Support, Data Optimization, Vendor Coordination, Platform Management

• Experience working in data, ETL, data security, and databases
• Strong coding skills in Python or Java/Scala, SQL
• Good knowledge of Spark, Airflow, Docker, CI/CD process
• Strong ability to reason about data structures, complexity, and possible engineering approaches to a problem
• Experience working with Cloud Platforms, AWS
• Experience maintaining data warehouses or data streaming platforms with traditional and NoSQL databases
• Experience in building end-to-end platforms/ solutions using both open source components and cloud vendor products

Qualifications: BS in Computer Science with 4 years of Experience

• Experience in end-to-end Data Quality, Data Profiling, Data Warehouse and reporting
• Proficient with one or more of the following languages including Java, Scala, Python, C#, JavaScript
• Strong experience in evaluating system performance and design, as well as its effect on data quality
• Deep knowledge in Relational Database Management Systems including complex SQL queries (ex., Microsoft SQL)
• Knowledge of best practices in Data Quality Management
• Demonstrated strong analytical skills
• Good English communication and coordination skills
• Strong communication skills (written& verbal) with all levels of the organization, and interpersonal skills
• Proficient with DevOps technologies and concepts for example, CI/CD, Docker, Kubernetes, Jenkins, TeamCity and Git
• Industry certification, such as DAMA CDMP, ICCP

Qualifications: BA in Information Systems with 6 years of Experience

• Experience in Python, R, Clojure, Julia or similar data-oriented 
• Experience with languages, including data frameworks like tidyverse or pandas, scikit, etc.
• Solid experience in SQL analytics (i.e, Postgres, BigQuery) (e.g. know how to use window functions and the nuances of using date ranges)
• Experience with data visualization tools
• Basic knowledge of big data technologies, e.g. Hadoop, Airflow, Kafka, Spark or similar
• Strong oral and communication skills with the proven ability to teach complex information effectively
• Knowledge of statistical analysis and/or machine learning
• Data Engineer Experience with customer data platforms like Segment and working with marketing teams
• Experience working in an online marketplace
• Experience with building programmatic SEO

Qualifications: BS in Software Engineering with 4 years of Experience

• Experience in systems analysis and programming of software applications
• Experience in managing and implementing successful projects
• Working knowledge of consulting/project management techniques/methods
• Ability to work under pressure and manage deadlines or unexpected changes in expectations or requirements
• Solid hands-on experience with data and databases
• Excellent interpersonal and communication skills
• Experience in troubleshooting code and logs
• Hands-on experience in scripting languages/programming
• Familiarity with REST, JDBC, SFTP, and Java
• Knowledge of Financial Markets and Products

Qualifications: BA in Statistics with 5 years of Experience

• Excellent understanding of TDD, agile development methodology and version control.
• Ability to function autonomously to solve problems and deliver working software. 
• Ability to communicate well with the team, both interactively and asynchronously, and that of being a positive, constructive team member.
• Expert knowledge of Python.
• Experience with blockchain systems.
• Experience with big data systems.
• Experience with CI/CD.
• Experience with Docker/Kubernetes or Serverless environments.
• Experience with SQS/SNS, Apache Kafka, RabbitMQ or other brokers.
• Experience with Apache Spark, Apache Flink, Ray.io and Airflow.
• Experience with public cloud providers, e.g. AWS, GCP, Azure, DigitalOcean, etc.

Qualifications: BS in Data Science with 7 years of Experience

• Experience/familiarity with other languages
• Experience with streaming technologies, eg, Kafka
• Experience with DBT, Spark,and  Beam
• Experience in designing data systems from scratch
• Experience with Terraform
• Familiarity with production quality ML and/or AI model development
• Experience working in startups
• Experience within crypto and/or fintech

Qualifications: BA in Applied Mathematics with 3 years of Experience

• Advanced knowledge of and experience with reporting packages, Tableau, Oracle OBIEE 12g, Power BI, and Splunk.
• Technical and project management skills as well as excellent PC and software application skills including Windows and Google Suite including Docs, Sheets, Slides, Drive as well as advanced knowledge of MS Office
• Strong analytical skills with the ability to collect, organize, analyze, and disseminate significant amounts of information with attention to detail and accuracy.
• Advanced SQL skills for use in developing reports, data analysis, issues research, and data quality assurance.
• Strong team player with experience working with business users.
• Verbal and written skills for inter-organizational communications.
• Ability to be highly organized and able to manage multiple, often conflicting priorities to successful completion.
• Advanced programming in Java and Python.
• Familiar with Machine Learning.

Qualifications: BS in Computer Engineering with 5 years of Experience

• Experience in building and maintaining data designs, validation rules, user interface, and workflow using Stibo Systems or other MDM/PIM software (i.e. Informatica, IBM MDM, Riversand, EnterWorks)
• Experience working with multiple database systems (Snowflake, Redshift, MySQL or similar)
• Experience developing and executing data migration processes
• Proficiency in JavaScript or another scripting language, and data modeling
• Experience with data integration tools (i.e., Matillion, Boomi, DataStage or similar), SQL query development and management, and cloud-based data warehouse experience
• Strong technical skills, problem-solving abilities, organizational skills, and detail orientation
• Communicates comfortably and effectively using the appropriate level of detail with all levels of the organization
• Ability to work in a highly collaborative and consensus-driven environment and comfortable with ambiguity and change in a fast-paced environment

Qualifications: BA in Business Analytics with 6 years of Experience

• Experience with web development using JavaScript/React
• Experience with the Django framework
• Experience with NoSQL databases like MongoDB/Redis.
• Experience with big data databases like BigQuery/Snowflake.
• Experience with big data streaming solutions like Kafka/Kinesis.
• High level of SQL and database optimization.
• Experience with 24/7 systems and real-time analytics.
• Experience working with Spark
• Experience with AWS
• Experience with monitoring and visualization tools such as Grafana, Prometheus, Data Dog, and Cloudwatch.

Qualifications: BS in Electrical Engineering with 4 years of Experience

• Prior experience with primary AWS services such as EC2, EMR, S3, IAM policies, Cloudwatch, Cloud Formation, SES
• Experience with data handling and database technologies (Lambda, DMS, Kafka, Spark, Redshift, Hadoop, Airflow, etc.).
• Experience with modern programming languages such as Python, Scala or Java.
• Experience designing and building systems to process large volumes of heterogeneous data, real-time and batch, to deliver data solutions.
• Command of advanced SQL queries and programming.
• Adopt best practices in data architecture, design and implementation.
• Ability to assimilate information and quickly discern the most relevant facts and recommend a creative, practical design solution. 
• Familiarity with DEVOPs tools and processes and CI/CD
• Excellent communication, presentation, influencing, and reasoning capabilities.
• Knowledge of legacy data warehousing tools and technology including Dimensional Models, Informatica PowerCenter, Informatica Cloud, MS Integration Services, Alteryx, Oracle, MS SQL Server etc.

Qualifications: BA in Computational Science with 5 years of Experience