Senior Data Engineer & Technical Delivery Lead (Python / Databricks)
Job Description
Senior Data Engineer & Technical Delivery Lead (Python / Databricks)
\nLocation: London (Hybrid – 2-3 days onsite)
\nContract: Initial 6 months
\n\nWe're currently supporting a major Investment Bank that's expanding its Data Engineering function and is looking to hire multiple contractors across Senior Data Engineer and Technical Delivery Lead level.
\nWhether you're a highly technical Senior Data Engineer looking to remain hands-on, or an experienced Technical Lead who enjoys combining delivery leadership with coding, we'd be keen to speak with you.
\nYou'll be joining a large-scale cloud data transformation programme, helping design, build and optimise enterprise data platforms using Python, Databricks and Spark within a modern Lakehouse environment.
\n\nKey Responsibilities
\n- \n
- Design, develop and maintain scalable data pipelines using Python and Databricks. \n
- Build, optimise and support enterprise ETL/ELT workflows using Apache Spark and Delta Lake. \n
- Design and develop robust data models and Lakehouse architectures. \n
- Implement and manage data workflows within the Databricks ecosystem. \n
- Ensure high levels of data quality, governance and pipeline reliability. \n
- Optimise performance across large-scale distributed data processing platforms. \n
- Collaborate with architects, product owners, analysts and engineering teams to deliver high-quality data solutions. \n
- Implement monitoring, logging and alerting across critical data platforms. \n
- Drive engineering best practice through code reviews, mentoring and technical collaboration. \n
- For Technical Delivery Lead opportunities, provide technical leadership, architectural oversight and end-to-end delivery of complex data engineering initiatives. \n
Required Skills & Experience
\n- \n
- Strong commercial experience developing data engineering solutions using Python. \n
- Extensive hands-on experience with Databricks, including Workflows, Notebooks and Delta Lake. \n
- Strong experience with Apache Spark / PySpark. \n
- Proven experience building scalable ETL/ELT pipelines. \n
- Strong SQL and data modelling skills. \n
- Experience designing modern Lakehouse architectures. \n
- Experience working with cloud platforms including AWS, Azure or GCP. \n
- Experience with modern data warehousing technologies such as Snowflake, Redshift or BigQuery. \n
- Experience with orchestration tools such as Airflow or Databricks Workflows. \n
- Previous experience working within Agile delivery environments. \n
Desirable Experience
\n- \n
- Databricks certifications. \n
- Kafka or Structured Streaming. \n
- CI/CD and DevOps practices. \n
- Docker and Kubernetes. \n
- Exposure to Machine Learning pipelines. \n
- Experience within Financial Services or other highly regulated environments. \n
About You
\nYou'll be an experienced Data Engineer or Technical Lead with a passion for building modern, scalable data platforms. Comfortable working in a collaborative Agile environment, you'll enjoy solving complex technical problems and delivering high-quality engineering solutions. If you're applying at Technical Delivery Lead level, you'll also bring strong leadership, stakeholder management and mentoring experience whilst remaining hands-on technically.
