Public summary
Seeking a Senior Data Analytics Engineer to design and deploy scalable data transformation pipelines and optimize data architectures. The role involves end-to-end pipeline management, performance tuning of AWS cloud services and data warehouses, and implementing software engineering best practices such as CI/CD and automated testing. Candidates should have strong Python and SQL skills, cloud experience with AWS, and a software engineering mindset. Flexible remote working with up to 3 months abroad per year is supported, alongside a competitive benefits package and professional development opportunities.
Responsibilities
Design, deploy, and maintain robust data transformation pipelines at TB scale including ingestion, transformation, testing, deployment, and monitoring; take ownership of data modeling and architecture; optimize legacy code and cloud compute costs; implement CI/CD workflows, containerization, and automated testing; develop data quality monitoring with alerts; mentor junior engineers and uphold technical standards within the team.
Qualifications
Minimum 4 years experience in Analytics or Data Engineering; advanced object-oriented Python programming; deep expertise in SQL and dbt for scalable data modeling; solid understanding of software engineering principles including version control, CI/CD, containerization; hands-on experience with AWS serverless architecture components; proven experience in automated testing for data pipelines; knowledge of data warehousing platforms and cost governance; Bachelor’s or Master’s in Computer Science, Engineering, Mathematics, or related fields preferred; familiarity with Infrastructure as Code (Terraform) and orchestration tools (Airflow, Dagster, Prefect) is advantageous.