
Senior Data Engineer
- London
- Permanent
- Full-time
- Collaborate effectively within a cross-functional, mission-led team, led by a product manager and engineering manager, contributing to the team's strategy, roadmap, and OKRs.
- Build and maintain data pipelines for ingesting and serving datasets to various downstream applications and data warehouses.
- Design and build evolvable, maintainable and reusable data models (both logical and physical) on strong engineering foundations to support business needs.
- Champion and ensure adoption of software engineering and data engineering best practices to build a well-engineered and well-governed data platform aligned with customer needs.
- Own technical solution design for complex features within your team, leading timely and successful implementation through your own and others' work.
- Enable continuous improvement efforts by identifying opportunities to enhance business value, improve cost efficiency, and increase the speed and quality of delivery.
- Mentor engineers within and outside your team by sharing best practices across the software development lifecycle, writing high-quality code, and contributing to a positive, feedback-driven team culture.
- Effectively partner with stakeholders and other teams to define and deliver the right solution for the right business problem statement.
- Cloud Data Warehouse - Snowflake
- AWS Data Solutions - Kinesis, SNS, SQS, S3, ECS, Lambda
- Data Governance & Quality - Collate & Monte Carlo
- Infrastructure as Code - Terraform
- Data Integration & Transformation - Python, DBT, Fivetran, Airflow
- CI/CD - Github Actions / Jenkins
- Business Intelligence - Looker
- Extensive experience in data engineering, including designing and maintaining robust data pipelines.
- Proficient in SQL and relational databases; familiarity with modern data warehousing solutions such as Snowflake is preferred.
- Proficient in programming, capable of developing and maintaining tested, production-ready data solutions, preferably in Python.
- Familiarity with major cloud providers and their data services, concrete experience in building production-grade data solutions on AWS is a plus.
- Experience in data modeling and warehouse architecture design.
- Experience with data orchestration and workflow management tools such as Airflow.
- Solid understanding of data ingestion, transformation, and ELT/ETL practices.
- Expertise on data transformation frameworks such as DBT.
- Experience with Infrastructure as Code (IaC) toolsTerraform preferred.
- Experience with version control systems, GitHub preferred.
- Experience with continuous integration and delivery (CI/CD) practices and tools, such as GitHub Actions.
- Ability to work independently as well as part of a team, understand and interpret functional and non-functional requirements.
- Strong communication skills and experience collaborating with technical and non-technical colleagues.
- A degree in a STEM field, e.g. Computer Science, Software Engineering, Mathematics.
- Familiarity with data integration tools such as Fivetran.