- 5+ years of programming and scripting experience with SQL, Python, and PySpark.
- 5+ Years - Ability to work effectively across organizations, product teams and business partners.
- 5+ Years - Knowledge Agile Methodology, experience in writing user stories
- 5+ Years Demonstrated ability to lead data engineering projects, design sessions and deliverables to successful completion.
- 2+ years of GCP Cloud experience with solutions designed and implemented at production scale.
- Knowledge of Data Warehouse concepts
- Experience with Data Warehouse/ ETL processes.
- Strong process discipline and thorough understating of IT processes (ISP, Data Security).
- Critical thinking skills to propose data solutions, test, and make them a reality.
- Deep understanding of data service ecosystems including data warehousing, lakes, metadata, meshes, fabrics and AI/ML use cases.
- User experience advocacy through empathetic stakeholder relationship.
- Effective Communication both internally (with team members) and externally (with stakeholders)
- Must be able to take customer requirements, conceptualize solutions, and build scalable/extensible systems that can be easily expanded or enhanced in the future.
Back to searchData Engineer
Trust In Soda
Posted 21 hours ago, valid for 22 days
London, Greater London EC1R 0WX
£45,000 - £54,000 per annum
Full Time
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Sonic Summary
- The role of Data Engineer requires a start date as soon as possible and is a 12-month contract position located in Essex with 1 day in the office and 4 days working from home.
- The pay rate for this position ranges from £300 to £321 per day on a PAYE basis.
- Candidates must have at least 5 years of programming and scripting experience with SQL, Python, and PySpark, along with experience in leading data engineering projects.
- Additionally, a minimum of 2 years of experience in GCP Cloud solutions at a production scale is required, along with knowledge of Data Warehouse concepts and ETL processes.
- The successful candidate will be responsible for building scalable data products and ensuring robust data infrastructure while collaborating effectively across various teams.
