Design and build data pipelines to support data science projects following software engineering best practices
Identify, design, and implement internal operational improvements: automating manual processes, optimizing data delivery, improving data quality, re-designing infrastructure for greater scalability, etc
Design and deploy high performance systems with reliable monitoring and logging practices and build reusable components, frameworks, and libraries at scale to support analytics products
Work with data scientists and analysts to productionize data pipelines and machine learning models, so that they can scale and accommodate various business requirements
Drive collaborative reviews of design, code, test plans and dataset implementation performed by other data engineers in support of maintaining data engineering standards
Ensure information security standards are maintained at all time
Programming/software development
Contributes to selection of the software development approach for projects, selecting appropriately from predictive (plan-driven) approaches or adaptive (iterative/agile) approaches.
Testing
Accepts responsibility for creation of test cases using own in-depth technical analysis of both functional and non-functional specifications (such as reliability, efficiency, usability, maintainability, and portability).
Creates traceability records, from test cases back to requirements.
Produces test scripts, materials, and regression test packs to test new and amended software or services.
People management
Mentor and develop data engineers in adopting best practices in virtual teams
Participates in reviews of own work and leads reviews of colleagues' work.
Create an inclusive working environment
Stakeholder management
Partner with the Global Operations business owners, project teams and colleagues at all levels, including senior stakeholders, ensuring their views and requirements are captured
Act as the ambassador for the data product, showcasing the key functionalities, driving adoption, and assuring operational excellence together with IT peers
Education & Professional experience
Bachelor’s and/or master’s degree, preferably in computer science (or the equivalent)