Data Engineer
- Design, build, and maintain robust ELT pipelines and transformation workflows
- Model and maintain curated data layers to support reporting, analytics, and decision-making
- Ensure high availability, scalability, and performance of data warehouse systems (cloud-based, e.g., Redshift)
- Collaborate with business and domain experts to define and deliver high-value, reusable data products
- Implement best practices around versioning, SLAs, data contracts, and quality validation
- Own the end-to-end lifecycle of key datasets, including documentation, testing, monitoring, and maintenance
- Use metadata, lineage, and usage metrics to ensure data products are trustworthy, discoverable, and valuable
- Build intuitive, well-structured data models to empower BI tools (e.g., QuickSight, Power BI, Tableau)
- Collaborate with analysts and domain users to promote adoption of self-serve analytics tools
- Create and maintain data dictionaries, technical and business catalogs, and user onboarding documentation
- Contribute to internal data enablement initiatives such as training and knowledge-sharing sessions
- Implement data access controls and support zero-trust security principles
- Support data classification, lineage, and automated data governance tooling
- Ensure compliance with internal and external data policies (e.g., GDPR)
- 3+ years of experience as a Data Engineer, with a strong focus on data warehousing and data modeling
- Hands-on experience with cloud-native data tech (preferably AWS: Redshift, Glue, S3, Lambda, IAM, Terraform, GitHub, CI/CD)
- Proficiency in SQL and Python for data processing and automation
- Experience working with data modeling tools and practices (e.g., dimensional, star/snowflake schema, dbt)
- Solid understanding of data governance, metadata, and quality frameworks
- Strong collaboration and communication skills, with the ability to work cross-functionally in an Agile environment
- Exposure to data product management principles (SLAs, contracts, ownership models)
- Familiarity with orchestration tools and observability platforms (Airflow, dbt, Monte Carlo, etc.)
- Exposure to real-time/streaming pipelines
- Understanding of information security best practices
- Familiarity with BI tools (QuickSight, Power BI, Tableau, Looker, etc.)
- Interest or experience in building internal data communities or enablement programs
- Working with diverse data sources (APIs, CRMs, SFTP, databases) and formats (Parquet, JSON, XML, CSV)
- Exposure to machine learning models or AI agents
- Help shape the future of data in an organization that treats data as a product
- Work in a modern data stack environment with a focus on real impact
- Be part of a collaborative, open, and empowering data culture
- Drive innovation in self-service analytics and data literacy
• Competitive salary & progression
• Open and inclusive culture
• Hybrid working
• Fantastic offices and great working environment
• Vitality Health Plan (includes private health insurance, travel insurance, gym discounts)
• Medicash health plan (Level 3)
• 5% employer pension contribution
• Life assurance
• Income protection insurance
• 28 days holiday plus 3 additional days, bank holidays & further days for various key life events
• Team socials
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