Data Engineer / Analytics Engineer – SQL,… at Antelope… · Kingswinf…

Salary: £35,000–£45,000 per annum
Location: Kingswinford, West Midlands
Job Type: Full-time, Permanent
Working Pattern: Fully office-based, Monday to Friday

About the Opportunity

We're recruiting for a hands-on Data Engineer / Analytics Engineer to join a growing business in Kingswinford.

This is an excellent opportunity for someone who enjoys getting stuck into the technical side of data, improving how information flows through a business and making sure data is accurate, reliable and ready for reporting.

You'll work within a small team, taking ownership of data pipelines, SQL transformations and reporting tables, while helping introduce and share good engineering practices.

We're looking for someone who can not only write good code but also explain technical problems, work with colleagues across the business and help find practical solutions.

What You'll Be Doing

• Building, maintaining and improving data pipelines and ETL/ELT processes.
• Writing, optimising and maintaining SQL queries and transformations.
• Working with data warehouses, including Google BigQuery.
• Using dbt or similar SQL-based transformation tools to create clean, structured, reporting-ready datasets.
• Developing and maintaining staging layers, transformation models and reporting tables/data marts.
• Using Git and GitHub for version control, collaboration, code reviews and safe deployment.
• Investigating data quality issues, validating outputs and troubleshooting problems.
• Supporting dashboards and reporting by ensuring the underlying data is accurate and accessible.
• Documenting data processes, business definitions and technical solutions.
• Sharing best practices and helping improve the way the business manages its data.

What We're Looking For

Essential experience:

• Strong commercial SQL skills, including joins, aggregations, CTEs and window functions.
• Practical experience building, maintaining or supporting data pipelines and ETL/ELT workflows.
• Experience working with and supporting a data warehouse.
• Hands-on experience transforming raw data into structured, reporting-ready datasets.
• Experience using Git and GitHub in a professional development environment.
• A good understanding of data modelling, data quality and testing.
• Previous commercial data experience within the UK.
• The ability to explain technical problems clearly and work collaboratively with technical and non-technical colleagues.
• A proactive, hands-on attitude and willingness to take ownership of problems.

Desirable experience:

• Google BigQuery or another cloud data warehouse such as Snowflake, Redshift or Azure Synapse.
• dbt (Data Build Tool) or an equivalent SQL-based data transformation/modelling approach.
• Python for scripting, automation or data processing.
• Power BI, Looker, Tableau or other reporting tools.
• Experience with CI/CD, automated testing and deployment.
• Experience sharing technical best practices or mentoring colleagues.
• NetSuite or other ERP systems.

The Right Person

You might currently be working as a Data Engineer, Analytics Engineer, SQL Developer or Data Warehouse Developer.

We're more interested in what you've actually built and supported than your exact job title or the industry you've worked in.

You'll enjoy being hands-on, solving problems, working across different areas of data engineering and contributing ideas. You'll be comfortable working in a small team where your contribution makes a visible difference.

This is a technical Data Engineering position rather than a purely reporting-focused Data Analyst role.

Pay: £35,000.00-£45,000.00 per year

Benefits:

• Free parking

Application question(s):

• Have you commercially built or maintained SQL-based data pipelines or transformations?
• Have you worked with a data warehouse in a commercial environment?
• Are you currently based within a reasonable commuting distance of Kingswinford (DY6) and able to work from the office five days per week?

Experience:

• professional GIT / GIThub: 1 year (required)

Work Location: In person