At a Glance
- Tasks: Design and develop scalable data solutions using Azure Databricks in an HR tech environment.
- Company: Join a forward-thinking company focused on innovative HR technology.
- Benefits: Hybrid work model, competitive salary, and opportunities for professional growth.
- Other info: Collaborative team environment with a focus on automation and cutting-edge technologies.
- Why this job: Make a real impact by building reliable data pipelines that enhance employee experiences.
- Qualifications: 8-10 years of data engineering experience with strong Azure Databricks skills.
The predicted salary is between 56250 - 68750 £ per year.
- Azure Databricks Data Engineer
- Working pattern: Hybrid – 3–4 days per week onsite
Role Overview
We are looking for an experienced Azure Databricks Data Engineer to design, develop and deliver scalable data solutions within an HR technology environment.
You will work across the employee lifecycle, building reliable data pipelines and analytics solutions with a strong focus on automation, testing, security and production quality.
Key Responsibilities
- Design and develop scalable data pipelines and analytics solutions using Azure Databricks and Azure Data Factory.
- Build and improve data products supporting HR and employee lifecycle processes.
- Translate business and technical requirements into production-ready solutions.
- Develop data lake, data warehouse and data mesh solutions using Azure services.
- Work with large, complex and multi-format datasets.
- Apply automated testing, CI/CD and Dev Ops practices throughout the development lifecycle.
- Build observability into solutions to monitor production health and support incident resolution.
- Ensure solutions meet security, reliability, compliance and performance standards.
- Collaborate with engineering, product, HR and other cross-functional teams.
- Contribute to technical decisions with long‑term scalability and sustainability in mind.
Essential Skills and Experience
- 8–10 years of hands‑on data engineering experience.
- Strong commercial experience with Azure Databricks and Azure Data Factory.
- Advanced Spark development using Python or Scala, alongside strong SQL skills.
- Experience with Azure Data Lake Storage Gen2 and Azure SQL or Postgre SQL.
- Strong understanding of Azure analytics services and Azure identity, including SPN, SAMI and UAMI.
- Experience designing data lake, data warehouse, data mesh and service‑oriented integration solutions.
- Previous ETL development experience using Informatica, SSIS, Talend or similar.
- Experience delivering solutions within an Agile SDLC environment.
- Strong Git, Git Lab or Git Hub experience, including branching, pull requests and CI/CD.
- Hands‑on scripting experience with Linux or Power Shell.
- Exposure to Docker and automated testing practices.
- Experience with pipeline orchestration tools such as Apache Airflow, Autosys or Control‑M, with Airflow preferred.
- Excellent written and verbal English communication skills.
Desirable Skills
- Kafka or other streaming technologies.
- Terraform, ARM templates, YAML or Puppet.
- Git Lab CI/CD pipeline creation.
- Azure Functions and Logic Apps.
- Test‑driven development.
- Previous experience delivering data solutions within an HR or employee lifecycle environment
- #J-18808-Ljbffr
Databricks Data Engineer employer: Coltech Recruitment
Coltech Recruitment is an exceptional employer that prioritises the growth and development of its team members. With a clear path to leadership and comprehensive training, employees can expect to become top-performing consultants in just 12–18 months. The vibrant London office fosters a collaborative work culture, offering exciting opportunities in the UK and EUR markets, making it a rewarding place for those seeking meaningful careers in recruitment.
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We think this is how you could land Databricks Data Engineer
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We think you need these skills to ace Databricks Data Engineer
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
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✨Brush Up on Your Statistics
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✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
