Data Engineer

eTeam; Milton Keynes; On-site; GBP 50,000 - 66,000; Full time

Job summary

eTeam in Milton Keynes is seeking an experienced Data Engineer to design, develop and support scalable data solutions across the enterprise. You will build data pipelines, APIs and cloud-based data products while ensuring data quality, governance and security.

You will work with Product Owners, Architects and stakeholders to deliver reliable, compliant data services, optimize SQL, and implement ETL/ELT pipelines using Azure, Informatica IDMC and related technologies in a regulated financial

Qualifications

• Hands-on experience designing, building and supporting scalable, governed data solutions.
• Proven ability to deliver data pipelines and API integrations.
• Experience in cloud data platforms (Azure) and data warehousing concepts.

Responsibilities

• Design, develop and support scalable, secure data solutions across VWFS.
• Deliver data pipelines, API integrations and cloud-based data products.
• Implement automated data quality controls and governance.
• Collaborate with Product Owners, Architects and stakeholders to ensure reliable data services.

Skills

SQL

Data engineering

Python

PySpark

Azure

Informatica IDMC

API integrations

ETL/ELT pipelines

Data modeling

Data governance

Git

CI/CD

Azure Data Factory

Databricks

MDM / Customer 360

Regulated industry knowledge

Agile

Troubleshooting

SQL performance tuning

Postman

Education

null

Tools

Postman

Git

Azure Data Factory

Databricks

Informatica IDMC

Oracle data warehouse

Job description

Location: Milton Keynes

Pay Rate: £313 per day all inc. (PAYE through Umbrella)

Days on site: 2-3 days/week in the office

Role Description:

• The Data Engineer is responsible for designing, developing and supporting scalable, secure and governed data solutions that enable trusted, high-quality data across VWFS.
• The role delivers data pipelines, API integrations, cloud-based data products and automated data quality controls using technologies such as SQL, Informatica IDMC, Azure and Oracle data warehouse platforms.
• Working closely with Product Owners, Architects and business stakeholders, the Data Engineer ensures data solutions are reliable, compliant and aligned to strategic business outcomes while supporting the ongoing operation and enhancement of enterprise data services.
• Strong SQL development and query optimisation skills.
• Experience designing, building and supporting ETL/ELT pipelines.
• Data integration experience across multiple source systems, file-based feeds and APIs.
• Experience using Postman to test, validate and troubleshoot REST APIs and data integrations.
• Experience developing and supporting cloud-based data solutions within Azure.
• Understanding of data modelling and physical data structures.
• Experience with data warehousing concepts, including staging, foundation and reporting layers.
• Experience implementing automated data quality controls, reconciliation processes and root cause analysis for data issues.
• Experience using Informatica IDMC for data integration, data quality, ingestion and orchestration.
• Understanding of data governance, lineage and enterprise architecture standards.
• Experience monitoring, troubleshooting and supporting production data pipelines.
• Experience using Git-based source control and collaborative development practices.
• Ability to collaborate with business stakeholders, architects and delivery teams.
• Understanding of data security, privacy and regulatory requirements when handling customer and financial data.
• Strong analytical and problem-solving skills.
• Ability to translate business requirements into technical solutions.
• Strong communication skills with the ability to explain technical concepts to technical and non-technical audiences.
• Experience documenting data solutions, data flows and operational procedures.
• Experience working in Agile delivery teams.
• Databricks or similar cloud data engineering platform experience.
• Azure Data Factory, Fabric or other cloud-native data engineering tools.
• Python or PySpark development.
• Experience with Master Data Management (MDM) and Customer 360 solutions.
• Experience with CI/CD pipelines and DevOps practices.
• Experience with Genesys, Salesforce or other customer-focused platforms.
• Financial Services or regulated industry experience.
• Knowledge of data observability and monitoring tools.
• Mentoring or technical leadership experience.