Data Engineer, People and Transformation
Found in: beBee S IN - 4 weeks ago
Join us as a Data Engineer
- If you’re ready to take on a collaborative role in shaping our data platform and support our purpose by helping our colleagues champion their potential, then we’d love to hear from you
- In this key role, you’ll be driving value for our customers by building data solutions
- Participating actively in the data engineering community, you’ll deliver opportunities to support the bank’s strategic direction while building your network across the bank
- We're offering this role at associate levelWhat you'll do
We’re launching a strategic programme to enhance our capabilities for People & Transformation data where you’ll design, develop, and implement a people data warehouse for colleagues, workforce, supply chain services, third party risk management data and create reusable data assets for the Group within one-bank architecture.
As a Data Engineer, you’ll be carrying out data engineering tasks to build, maintain, test and optimise a scalable data architecture, as well as carrying out data extractions, transforming data to make it usable to data analysts and scientists, and loading data into data platforms.
You’ll also be:
- Developing comprehensive knowledge of the bank’s data structures and metrics, advocating change where needed for product development
- Building automated data engineering pipelines through the removal of manual stages
- Collaborating closely with core technology and architecture teams in the bank to build data knowledge and data solutions
- Developing a clear understanding of data platform cost levers to build cost effective and strategic solutions
- Sourcing new data using the most appropriate tooling and integrating it into the overall solution to deliver for our customers
- Working in an agile way within multi-disciplinary data and analytics teams to achieve agreed project and scrum outcomesThe skills you'll need
We’re looking for Data Engineers who have experience in Amazon Web Services, Snowflake, SQL, Informatica, Apache Airflow and Agile methodologies. Along with this, you’ll need a good understanding of data usage and dependencies with wider teams and the end customer, as well as experience of extracting value and features from large scale data.
You’ll also demonstrate:
- Experience in building pipelines for a data warehouse using ETL methods, including data quality testing, cleansing and monitoring, and data warehousing and data modelling capabilities
- Extensive experience using SQL and Snowflake, alongside knowledge of data engineering fundamentals
- Good knowledge of modern code development practices
- Experience in Python, Kafka and Streamsets
- Strong communication skills with the ability to proactively engage with a wide range of stakeholders
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