At a Glance
- Tasks: Own and enhance a Databricks platform, improving data quality and reliability.
- Company: Join a forward-thinking company prioritising data-driven decision-making.
- Benefits: Competitive salary, flexible work, and opportunities for professional growth.
- Other info: Dynamic role with ownership and influence over critical data processes.
- Why this job: Make a real impact on data practices and shape the future of data usage.
- Qualifications: Experience with Databricks, SQL, and data engineering in cloud environments.
The predicted salary is between 55000 - 55000 £ per year.
Salary: £50K - £60K
Location: Manchester (3 days per week)
Role Overview:
Our client is looking for a Data Engineer to take ownership of a Databricks platform and help push it into its next stage of maturity. This is a great opportunity for someone who enjoys more than just building pipelines. The role is focused on improving data quality, strengthening platform reliability, developing clearer Bronze, Silver and Gold data layers, and creating trusted datasets that can support reporting, analytics and wider business decision-making. You'll be joining a business where data is becoming increasingly important, with the opportunity to shape how data is structured, governed and used across the organisation.
Key Responsibilities:
- Maintain, improve and optimise an existing Databricks data platform.
- Build and enhance scalable data pipelines using Spark, SQL and Python or Scala.
- Develop and mature Bronze, Silver and Gold layers to support analytics, reporting and downstream data use.
- Ingest and integrate data from APIs, databases and other source systems.
- Design data quality rules, validation checks and exception reporting to improve trust in business data.
- Investigate data issues, identify root causes and implement fixes that prevent recurring problems.
- Work with analysts, BI developers and business stakeholders to understand data requirements and turn them into practical engineering solutions.
- Support the design of curated data models for reporting and analytical consumption.
- Monitor workflow performance, troubleshoot failures and improve the reliability of data processes.
- Contribute to better documentation, governance, naming standards, lineage and data access practices.
- Identify opportunities to automate, simplify and standardise data engineering workflows.
What We're Looking For:
- Proven experience as a Data Engineer within a cloud-based data environment.
- Strong hands-on experience with Databricks and Apache Spark.
- Experience building or improving medallion architecture, including Bronze, Silver and Gold data layers.
- Strong SQL skills for transformation, validation and data analysis.
- Python or Scala experience for data engineering, automation or scripting.
- Experience extracting, ingesting and integrating data from APIs.
- Good understanding of data quality, data controls and reliability within production data environments.
- Experience working with cloud data services, ideally Azure, although AWS or GCP experience would also be relevant.
- Exposure to Delta Lake, Databricks Workflows, scheduling tools or lakehouse environments would be beneficial.
- An understanding of Power BI, reporting data models, governance, cataloguing or lineage would be useful.
- Strong communication skills, with the ability to work with technical and non-technical stakeholders.
Why Consider This Role?
This is a strong opportunity for a Data Engineer who wants more ownership, more influence and more impact than a standard pipeline-focused role. You'll be working on a business-critical Databricks platform where data quality, structure and reliability genuinely matter. The business is investing in better data practices, so this role offers the chance to improve how data is ingested, transformed, monitored and made available to the wider organisation. It would suit someone who enjoys solving messy data problems, building robust engineering patterns and helping create a platform that people across the business can trust.
Data Engineer - Databricks in Manchester employer: Akkodis
Join a forward-thinking company in Manchester as a Data Engineer, where you'll have the opportunity to take ownership of a critical Databricks platform and make a real impact on data quality and governance. With a strong emphasis on employee growth, collaborative work culture, and innovative data practices, this role offers a unique chance to shape the future of data within the organisation while enjoying a flexible work environment. The company values your contributions and provides a supportive atmosphere for tackling complex data challenges.
StudySmarter Expert Advice🤫
We think this is how you could land Data Engineer - Databricks in Manchester
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with people on LinkedIn. 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 projects, especially those involving Databricks, Spark, and data pipelines. This gives potential employers a taste of what you can do beyond just a CV.
✨Tip Number 3
Prepare for interviews by brushing up on common data engineering questions and scenarios. Practice explaining your thought process when tackling data quality issues or building scalable pipelines.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who take that extra step to engage with us directly.
We think you need these skills to ace Data Engineer - Databricks in Manchester
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the Data Engineer role. Highlight your experience with Databricks, Spark, and any relevant cloud services like Azure. We want to see how your skills match what we're looking for!
Showcase Your Projects:Include specific projects where you've built or improved data pipelines, especially using Bronze, Silver, and Gold layers. This gives us a clear picture of your hands-on experience and problem-solving skills.
Be Clear and Concise:When writing your application, keep it clear and to the point. Use bullet points for key achievements and responsibilities. We appreciate straightforward communication, especially when it comes to technical details!
Apply Through Our Website:Don't forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it makes the whole process smoother for everyone involved.
How to prepare for a job interview at Akkodis
✨Know Your Databricks Inside Out
Make sure you brush up on your Databricks knowledge before the interview. Be ready to discuss how you've used it in past projects, especially focusing on building and optimising data pipelines. Highlight any experience with medallion architecture and how you've improved data quality.
✨Showcase Your Problem-Solving Skills
Prepare examples of how you've tackled messy data issues in the past. Think about specific challenges you've faced, the steps you took to resolve them, and the impact your solutions had on the business. This will demonstrate your ability to think critically and act decisively.
✨Communicate Clearly with Stakeholders
Since this role involves working with both technical and non-technical stakeholders, practice explaining complex data concepts in simple terms. Be ready to discuss how you've collaborated with analysts or BI developers to turn data requirements into practical engineering solutions.
✨Emphasise Your Automation Experience
Talk about any opportunities you've identified for automating or simplifying data workflows. Share specific examples of how you've implemented these changes and the benefits they brought to your previous teams. This shows that you're proactive and always looking to improve processes.
