Data Engineer
- Discuss this with your agent
- Open in Claude
- Open in ChatGPT
Role details
Tech stack
Job description
Could you develop a variety of solutions from smaller proof of concepts through to production ready data systems with a focus on business benefit realisation? What will a day in the life of a Data Engineer involve?
- Develop data pipelines and functionality using agreed standards with approved methods and tooling, and support our partners doing the same where development activities are outsourced.
- Apply frameworks and patterns to support and maintain software and services, ensuring they are well-managed, monitored, maintained up-to-date, secure, performant, and available to users, and are supported by operational runbook.
- Capture and analyse user stories so that the user- and business-needs are well-understood, and our services have meaningful impact.
- Design, develop, and maintain robust data pipelines to ensure the efficient flow of data across various systems and platforms.
- Implement data models and schemas to support analytical and reporting needs.
- Build and maintain data warehouses, ensuring data quality, integrity, and security.
Requirements
Do you have experience in Waterfall?, * Good understanding of database technology with specific use when storing and manipulating large datasets. (hundreds of millions of transactions)
- Good understanding and knowledge of general ETL/ELT principles and best practice.
- Understand industry recognised standard data models with a specific emphasis on the Kimball Dimensional Modelling approach.
- Proven experience of interpreting business requirements, then creating and implementing technical solutions and data briefs as a result.
- Proven experience of managing projects effectively, using both waterfall and agile approaches.
- Experience developing data pipelines using Azure Databricks, dbt or snowflake (or similar tools) and coding in SQL and Python.
Benefits & conditions
Pulled from the full job description
- Flexitime
- Annual leave
- Employee assistance programme
- Company pension, Salary: £39,541 to £45,000 per annum (plus ILW, if residing & working in London) Hours: 35 per week, flexible Contract: Permanent Could you help us act upon the latest data and insights to design our services, partner and convene, raise income and advocate for change?
Could you implement the design to develop and deliver the databases, data processes, data products and services that make up the data platform?, In return for your commitment and expertise, you’ll get:
- Flexible working: Remote and hybrid working, flexitime, compressed hours, and job sharing.
- Holidays: 36 days annual leave (including bank holidays) + option to buy 5 extra days.
- Pension scheme: Up to 6% contributory pension.
- Learning & Development: A range of career & learning opportunities.
- Discounts: Blue Light Discount Card, Tickets For Good & employee benefits platform..
- Wellbeing Support: Peer Supporters, CiC (EAP) & Headspace App.
- Cycle2Work: Lease a bicycle through the scheme.
We are dedicated to building an inclusive, equitable and wellbeing focused culture where everyone feels safe, valued and can thrive. Guided by our Equity, Diversity, Inclusion and Wellbeing Strategy, we foster belonging, psychological and physical wellbeing, and work to remove barriers to fair opportunities. Grounded in compassion and anti racist practice, we listen to diverse voices, value lived experience and create environments where staff and volunteers can succeed. Join us and be part of an organisation that leads with care, celebrates difference and helps everyone succeed. Together, we are the world’s emergency responders
Apply for this position
This job is hosted externally. Click below to view the full posting and apply.
Apply on indeed.comGood distractions
Talks and stories from around this role — technically off-topic, practically not.
Moments
Explore playlistsVideos
See allRelated articles
See all
Data Analyst Salary in the UK
Top Big Data Technologies That You Need to Know
Software Engineer Salary London
Making Data Warehouses Fast: A Developer’s Story