At a Glance
- Tasks: Design and maintain scalable data pipelines using Databricks, SQL, Spark, and Python.
- Company: Join a forward-thinking company that values innovation and collaboration.
- Benefits: Enjoy competitive pay, flexible work options, and opportunities for professional growth.
- Other info: Be part of a dynamic team with a commitment to equality and diversity.
- Why this job: Make a real impact by working on cutting-edge data projects and AI use cases.
- Qualifications: Experience as a Data Engineer with strong skills in Databricks and data transformation.
The predicted salary is between 60000 - 80000 £ per year.
Responsibilities
- Design, build, and maintain scalable, production‑grade data pipelines into Databricks.
- Implement ingestion, transformation, and optimisation patterns using SQL, Spark, and Python.
- Ensure datasets are performant, reliable, and analytics‑ready.
- Lead hands‑on data mapping from legacy systems into Databricks with downstream implications for Analytics (Tableau) and strong AI use cases (Mulesoft IDP and Data360/Agentforce).
- Support ingestion and harmonisation of data arising from M&A activity.
- Analyse acquired datasets and integrate them into the central data platform.
- Establish and govern testing standards covering functional, regression, integration, and UAT testing.
- Implement data quality checks, validation rules, and monitoring within pipelines.
- Support governance standards defined by the Data & Analytics Manager.
- Ensure high-quality documentation and data governance.
- Work with internal and external teams, using Agile delivery and Project Management tools such as Jira/Confluence/Miro.
Requirements
- Commercial experience as a Data Engineer in a modern data platform.
- Strong hands‑on experience with Databricks (or equivalent cloud data platforms).
- Experience mapping and migrating data from legacy systems.
- Solid understanding of data modelling and transformation.
- Experience supporting analytics tools such as Tableau.
- Desirable: Experience with Salesforce Data Cloud (Data 360) or CRM data models.
- Desirable: Exposure to AI‑ready data platforms or automation use cases.
- Desirable: Experience working within a Centre of Excellence or multi‑team environment.
Success Measures
- Reliability of data pipelines (uptime, successful run rates).
- Time taken to onboard new data sources.
- Reduction in downstream data issues and rework.
- Adoption of engineered datasets by analytics and AI use cases.
- Quality and clarity of data documentation and mappings.
Core Values
- Aspire: Challenge convention, be entrepreneurial with energy for change. Be the best we can be.
- Innovate: Creatively evolve our working practices, use our revenue and resources in a virtuous cycle of improving our people, systems, and growth.
- Integrate: Bring together people and systems into a cohesive force.
- Commitment: Work with integrity and invest in long-term relationships, creating a strong market position and delivering sustained commercial advantage.
Equality and Diversity
This organisation strives to operate a policy of equal opportunity and to not discriminate against any person because of sex, race, colour, or national origin.
Data Platform Engineer - Databricks & Analytics Pipelines in Peterborough employer: Taylor Rose TTKW Limited
As a Data Platform Engineer at our innovative company, you will thrive in a dynamic work culture that champions creativity and collaboration. We offer competitive benefits, a commitment to employee growth through continuous learning opportunities, and the chance to work on cutting-edge projects in a supportive environment. Located in a vibrant area, our team is dedicated to fostering an inclusive atmosphere where your contributions are valued and recognised.
StudySmarter Expert Advice🤫
We think this is how you could land Data Platform Engineer - Databricks & Analytics Pipelines in Peterborough
✨Tip Number 1
Network like a pro! Reach out to folks in your industry on LinkedIn or at meetups. We all know that sometimes it’s not just what you know, but who you know that can help you land that Data Platform Engineer role.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data pipelines and projects using Databricks, SQL, and Python. We want to see your hands-on experience, so make sure it’s easy for potential employers to see what you can do.
✨Tip Number 3
Prepare for those interviews! Brush up on your technical knowledge and be ready to discuss your experience with data mapping and analytics tools like Tableau. We recommend practising common interview questions related to data engineering.
✨Tip Number 4
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 Data Platform Engineer - Databricks & Analytics Pipelines in Peterborough
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the Data Platform Engineer role. Highlight your experience with Databricks, SQL, and Python, and don’t forget to mention any relevant projects that showcase your skills in building data pipelines.
Showcase Your Experience:In your cover letter, give us a glimpse of your hands-on experience with data mapping and migration from legacy systems. We love seeing real-world examples, so share specific challenges you faced and how you overcame them!
Emphasise Collaboration:Since we work closely with internal and external teams, it’s important to highlight your experience in collaborative environments. Mention any tools like Jira or Confluence that you've used to manage projects and keep everyone on the same page.
Be Authentic:Let your personality shine through! We value authenticity and want to know what drives you. Share your passion for data engineering and how you align with our core values of aspiration, innovation, integration, and commitment.
How to prepare for a job interview at Taylor Rose TTKW Limited
✨Know Your Tech Stack
Make sure you’re well-versed in Databricks, SQL, Spark, and Python. Brush up on your knowledge of data pipelines and how to optimise them. Being able to discuss specific projects where you've implemented these technologies will really impress the interviewers.
✨Showcase Your Problem-Solving Skills
Prepare examples of how you've tackled challenges in data mapping or migration from legacy systems. Highlight your analytical skills and how you’ve ensured data quality and reliability in past projects. This will demonstrate your hands-on experience and ability to think critically.
✨Familiarise Yourself with Agile Practices
Since the role involves working with Agile delivery and tools like Jira and Confluence, be ready to discuss your experience in these areas. Share how you’ve collaborated with teams in a multi-team environment and how you’ve contributed to project management processes.
✨Emphasise Your Commitment to Quality
Talk about your approach to documentation and data governance. Be prepared to explain how you’ve established testing standards and data quality checks in previous roles. This shows that you value high-quality work and understand its importance in data engineering.
