Data Engineer: Databricks Pipelines for Impact (Flexible)

CO-OP; United States; Hybrid; USD 120,000 - 180,000; Full time

Benefits offered by this job

Annual bonus

28 days holiday (32 with service)

Pension with up to 10% employer contr.

onsite gym access (Manchester HQ)

Discount on Co-op products

Stream - early access to pay

Virtual healthcare

24/7 support

Training and career progression

Cycle-to-work

Job summary

Co-op is seeking an experienced Data Engineer to help build a new data platform on Databricks, enabling advanced data science, analytics, and BI across Food Retail, Funeralcare, and Insurance. You will code primarily in Python and SQL, collaborating with partners to translate data problems into scalable solutions.

The role emphasizes hands-on pipeline development, cloud data platform work, and contributing to the data architecture roadmap.

Qualifications

• Significant experience as a Data Engineer delivering modern data architectures in a multi-disciplinary team
• Experience using Python and SQL
• Excellent organisation, communication, and collaboration skills
• Able to work in an agile environment with changing priorities
• Curious about emerging technologies and solving complex business problems

Responsibilities

• Collaborate with partners across the wider Co-op to understand data problems and design solutions that satisfy business needs
• Develop, build and maintain enterprise data solutions within our cloud data platform, building automation and quality into everything we do
• Hands-on development of data pipelines using Databricks, PySpark and SQL
• Help to develop and implement our data architecture and engineering roadmap across our data teams

Skills

Data engineering

Python

SQL

Agile

Communication

Collaboration

Databricks

PySpark

Tools

Databricks

PySpark

Job description

Co-op is seeking an experienced Data Engineer to help build a new data platform on Databricks, enabling advanced data science, analytics, and BI across Food Retail, Funeralcare, and Insurance. You will code primarily in Python and SQL, collaborating with partners to translate data problems into scalable solutions.

The role emphasizes hands-on pipeline development, cloud data platform work, and contributing to the data architecture roadmap.