Overview
Peaple Talent are working with a data consultancy who partner with a range of enterprise clients to deliver modern cloud data platforms. They’re currently looking for a Databricks Data Engineer to support multiple client engagements across large-scale data transformation programmes.
The Role
This is a hands-on Databricks Data Engineering contract where you’ll be working across different client environments, helping design, build and optimise scalable data platforms.
You’ll be focused on delivering robust data pipelines and analytics-ready datasets using Databricks, working across cloud environments such as Amazon Web Services or Microsoft Azure depending on the client. The work will range from greenfield builds through to modernisation of existing data estates.
- Design and build scalable data pipelines using Databricks
- Develop and optimise ETL/ELT workflows using Spark (PySpark/SQL)
- Support migration and modernisation of legacy data platforms into Databricks
- Improve performance, reliability and cost efficiency across data workloads
- Work closely with Data Engineers, Analysts and Architects across client teams
- Implement data quality, governance and best practices across delivery
What We’re Looking For
- Strong hands-on experience with Databricks in a Data Engineering capacity
- Solid experience with Spark (PySpark / Spark SQL)
- Proven track record building and optimising data pipelines (ETL/ELT)
- Experience working within cloud environments (AWS or Azure)
- Strong SQL skills and experience working with large-scale datasets
- Familiarity with orchestration tools such as Airflow or similar
- Good understanding of data modelling and distributed data processing concepts
- Comfortable working across multiple client environments and stakeholders
What’s on Offer
- Location: London
- Remote working: 3 days a week onsite
- Initial 6-month contract (strong likelihood of extension)
- Exposure to multiple enterprise data transformation programmes
- Opportunity to work across a variety of Databricks implementations within a consultancy environment
#J-18808-Ljbffr