Das ist der Job
Ensure technical solutions, pipelines and data models are fit for purpose.
Darum lohnt es sich
Lead technical and solution design sessions within an agile development team. Influence and champion the vision for data engineering across several Lending teams. Use modern data engineering practices and Data Vault 2.0 methodologies to design, build, and maintain ETL data pipelines.
Responsibilities Develop, test, and deploy high-quality code using Python, PySpark, and SQL in a cloud-based environment. Collaborate closely with product owners, analysts, architects, and internal data consumers across Reporting, Risk, and Finance. Act as an informal technical leader by mentoring and coaching developers.
Improve pipeline reliability and maturity by enhancing automation, integration testing, and CI practices across the data development lifecycle. Qualifications Bachelor’s degree in computer science or software engineering. Minimum 10 years of software development experience (or an equivalent combination of education and experience).
Expert-level proficiency in AWS technologies: AWS Glue, Step Functions, S3, Redshift, Quicksight, Lambda, Eventbridge, Sagemaker, and AppFlow. Expert-level proficiency in Python and/or PySpark. Extensive experience designing and building ETL data pipelines. Data modelling experience in Data Vault 2.0 and Dimensional (Star Schema) methodol
