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- Tasks: Lead the design and operation of scalable data pipelines using Python on Databricks.
- Company: Join a forward-thinking tech company focused on data innovation.
- Benefits: Attractive salary, flexible work options, and opportunities for professional growth.
- Other info: Collaborative environment with a focus on mentorship and career advancement.
- Why this job: Make a real impact by delivering high-quality datasets for analytics and ML.
- Qualifications: 8-12 years in data engineering with strong skills in Python, SQL, and AWS.
The predicted salary is between 70000 - 90000 £ per year.
We are seeking a Senior Data Engineer to lead the design, build, and operation of scalable data pipelines and domain-aligned data products on Databricks using Python. This role is accountable for delivering governed, discoverable, high‑quality datasets and services aligned to data mesh principles (domain ownership, product thinking, and federated governance), enabling analytics and ML use cases with strong reliability, security, and performance.
Responsibilities
- Architect and deliver end‑to‑end data engineering solutions on Databricks (Spark/Delta Lake) using Python and SQL.
- Build data products aligned to data mesh principles: clear contracts, documentation, metadata, lineage, access controls, and measurable SLAs/SLOs.
- Develop and optimize batch and streaming pipelines with strong data quality checks and observability.
- Implement curated data layers and models (e.g., bronze/silver/gold as appropriate), including partitioning, file sizing, clustering strategies, and query optimization.
- Establish engineering standards: code quality, unit/integration testing, CI/CD, release governance, and reusable frameworks.
- Partner with governance, security, and platform teams to ensure compliance with firm policies (RBAC, encryption, retention, auditability) and smooth onboarding of consumers.
- Provide technical leadership across squads: architecture reviews, mentoring, and hands‑on delivery for critical components.
- Use AI tools for tasks such as code scaffolding, refactoring, test generation, documentation, and troubleshooting, with human validation and adherence to internal controls.
- Promote responsible adoption patterns within the team (e.g., prompt hygiene, avoiding sensitive data exposure, and ensuring outputs meet quality/security standards).
Qualifications
- 8‑12+ years of experience in data engineering / software engineering with end‑to‑end delivery ownership.
- Strong hands‑on expertise with AWS, Databricks and Delta Lake.
- Strong Python engineering skills (modular design, packaging, testing, dependency management).
- Strong SQL and data modeling fundamentals.
- Solid Spark fundamentals (joins, shuffle, partitioning, caching, skew handling, cluster sizing).
- Experience implementing CI/CD and SDLC best practices (Git‑based workflows, code reviews, automated testing).
- Proven stakeholder management and ability to drive cross‑team delivery.
Software Engineer III - Senior Data Engineer employer: Jpmorgan Chase & Co.
Contact Detail:
Jpmorgan Chase & Co. Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Software Engineer III - Senior Data Engineer
✨Tip Number 1
Network like a pro! Reach out to your connections in the industry, attend meetups, and engage with online communities. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data engineering projects, especially those using Databricks and Python. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and soft skills. Practice common interview questions related to data engineering and be ready to discuss your past projects and how they align with the role.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are proactive about their job search!
We think you need these skills to ace Software Engineer III - Senior Data Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that match the job description. Highlight your expertise in data engineering, Python, and Databricks to show us you’re the right fit for the role.
Craft a Compelling Cover Letter: Use your cover letter to tell us why you’re passionate about data engineering and how your experience aligns with our needs. Be specific about your achievements and how they relate to the responsibilities listed in the job description.
Showcase Your Projects: If you've worked on relevant projects, don’t hesitate to include them! We love seeing practical examples of your work, especially those that demonstrate your ability to build scalable data pipelines and adhere to data mesh principles.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it’s super easy!
How to prepare for a job interview at Jpmorgan Chase & Co.
✨Know Your Tech Stack Inside Out
Make sure you’re well-versed in the technologies mentioned in the job description, especially Databricks, Python, and SQL. Brush up on your Spark fundamentals too, as they’ll likely ask you about joins, partitioning, and caching strategies.
✨Showcase Your Data Engineering Projects
Prepare to discuss specific projects where you've designed and built data pipelines. Highlight your experience with batch and streaming data, and be ready to explain how you ensured data quality and observability in those projects.
✨Understand Data Mesh Principles
Familiarise yourself with data mesh concepts like domain ownership and product thinking. Be prepared to discuss how you’ve applied these principles in your previous roles, particularly in relation to documentation and access controls.
✨Demonstrate Leadership and Collaboration Skills
Since this role involves technical leadership, think of examples where you’ve mentored others or led cross-team initiatives. Show that you can partner effectively with governance and security teams to ensure compliance and smooth onboarding.