At a Glance
- Tasks: Design and optimise data pipelines using Python and Databricks in a cloud transformation programme.
- Company: Join a leading Financial Services organisation with a focus on data engineering.
- Benefits: Hybrid work model, competitive pay, and opportunities for professional growth.
- Other info: Collaborative environment with a focus on engineering best practices and career advancement.
- Why this job: Be part of a cutting-edge data transformation project that makes a real impact.
- Qualifications: Strong experience in Python, Databricks, and building scalable data solutions.
The predicted salary is between 70000 - 90000 £ per year.
Senior Data Engineer & Technical Delivery Lead (Python / Databricks)
Location
London (Hybrid - 2-3 days onsite)
Contract
Initial 6 months
We're currently supporting a major Financial Services organisation that's expanding its Data Engineering function and is looking to hire multiple contractors across
Senior Data Engineer and
Technical Delivery Lead level.
Whether 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.
You'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.
Key Responsibilities
- Design, develop and maintain scalable data pipelines using Python and Databricks.
- Build, optimise and support enterprise ETL/ELT workflows using Apache Spark and Delta Lake.
- Design and develop robust data models and Lakehouse architectures.
- Implement and manage data workflows within the Databricks ecosystem.
- Ensure high levels of data quality, governance and pipeline reliability.
- Optimise performance across large-scale distributed data processing platforms.
- Collaborate with architects, product owners, analysts and engineering teams to deliver high-quality data solutions.
- Implement monitoring, logging and alerting across critical data platforms.
- Drive engineering best practice through code reviews, mentoring and technical collaboration.
- For Technical Delivery Lead opportunities, provide technical leadership, architectural oversight and end-to-end delivery of complex data engineering initiatives.
- Required Skills & Experience
- Strong commercial experience developing data engineering solutions using
- Python
- Extensive hands-on experience with
- Databricks
, including Workflows, Notebooks and Delta Lake.
- Strong experience with
- Apache Spark / Py Spark
- Proven experience building scalable ETL/ELT pipelines.
- Strong SQL and data modelling skills.
- Experience designing modern Lakehouse architectures.
- Experience working with cloud platforms including AWS, Azure or GCP.
- Experience with modern data warehousing technologies such as Snowflake, Redshift or Big Query.
- Experience with orchestration tools such as Airflow or Databricks Workflows.
- Previous experience working within Agile delivery environments.
Desirable Experience
- Databricks certifications.
- Kafka or Structured Streaming.
- CI/CD and Dev Ops practices.
- Docker and Kubernetes.
- Exposure to Machine Learning pipelines.
- #J-18808-Ljbffr
Senior Data Engineer & Technical Delivery Lead Python / Databricks - Venn Group employer: eFinancialCareers
Quilter plc is an exceptional employer, offering a dynamic work environment in Southampton where innovation and collaboration thrive. With a strong commitment to employee growth, comprehensive benefits including a generous holiday allowance and a non-contributory pension scheme, Quilter fosters a culture of inclusivity and continuous improvement, empowering employees to make meaningful contributions to the financial futures of their clients and communities.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Data Engineer & Technical Delivery Lead Python / Databricks - Venn Group
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Got some cool data science projects? Showcase them on platforms like GitHub or create a personal portfolio website. This visibility is crucial for landing temporary roles—let recruiters see your actual skills in action, which can set you apart from the crowd.
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We think you need these skills to ace Senior Data Engineer & Technical Delivery Lead Python / Databricks - Venn Group
Some tips for your application 🫡
Highlight Your Data Projects:When applying for a temporary data science role at eFinancialCareers, make sure to showcase any relevant projects you've worked on. Whether it's a personal project, an academic undertaking, or contributions to an open-source initiative, detailing these experiences can really set you apart and demonstrate your practical skills.
Emphasise Your Analytical Skills:In your CV and cover letter, focus on the specific analytical skills that are key to data science. Mention any experience with statistical tools, programming languages like Python or R, and data visualisation software. Don't forget to include any certifications that may bolster your expertise!
Show Your Flexibility:Since this is a temporary role, it's important to convey your adaptability and willingness to learn. In your cover letter to eFinancialCareers, emphasise how quickly you can get up to speed with new tools or projects. Highlight any previous experiences where you've had to adjust to new environments or challenges.
Craft a Unique Data-Driven Cover Letter:Instead of the usual generic cover letter, spice it up with some data! Maybe you’ve improved a process by 20% in a past role or cleaned a dataset with over a million entries. Use these stats to your advantage to grab eFinancialCareers’s attention and show the tangible impact of your work.
How to prepare for a job interview at eFinancialCareers
✨Showcase Your Analytical Skills
For a data science gig, it's crucial to demonstrate your analytical abilities. Be ready to discuss previous projects and the methodologies you used. Think about how you can quantify your impact—did your analysis improve efficiency or save costs? These are the stories that will stick with interviewers at eFinancialCareers.
✨Brush Up on Technical Skills
You might face technical questions on tools relevant to data science, like Python, R, or SQL. Prepare to solve a problem live—perhaps they'll ask you to write a simple query or code snippet. It’s cool to talk about them, but we need to show we can do it in practice, especially in a temporary role where quick results matter.
✨Highlight Your Adaptability
Since this is a temporary position, emphasise your ability to learn quickly and adapt to new tools or workflows. Share examples of how you've thrived in fast-paced environments before, and how you can hit the ground running at eFinancialCareers.
✨Prepare a Portfolio of Your Work
Bring your portfolio to the table—showcase projects where you've leveraged data science techniques to solve problems. Whether it’s a GitHub repository or a set of case studies, having tangible examples of your work will help you stand out and show what you bring to the team at eFinancialCareers.
