Data Engineer

Summary: The Data Engineer role involves accessing and analyzing organizational data to support various teams and projects. The position requires a blend of functional, data, and technical skills to optimize data architecture and ensure effective data delivery. Responsibilities include building data pipelines, performing complex data analysis, and improving data solutions to meet business needs. The ideal candidate will have a strong background in SQL and data engineering practices, with a focus on data quality and governance.

Key Responsibilities:

• Gain access to data across the organization and provide ongoing analysis of the data by monitoring, profiling, and analyzing databases.
• Understand business requirements, translate them into information needs, and implement those requirements using available data.
• Responsible for expanding and optimizing data architecture, as well as optimizing data flow and collection for cross-functional teams.
• Support software developers, database architects, data analysts, and data scientists on data initiatives and ensure optimal data delivery architecture is consistent throughout ongoing projects.
• Assemble large, complex data sets that meet functional/non-functional business requirements.
• Strong knowledge of SQL required. Ability to identify sets and subsets of information across multiple joins or unions of tables is preferred in addition to writing and troubleshooting SQL queries for data mining.
• Perform complex data analysis and investigation for customer requests to explain results and make appropriate recommendations.
• Strong understanding of data modeling concepts.
• Problem solver with the initiative to think critically to identify improvement opportunities (error detection, error correction, root cause analysis).
• Understand ETL that will aid in verification and testing of data.
• Build processes supporting data transformation, data structures, metadata, dependency, and workload management.
• A successful history of manipulating, processing, and extracting value from large disconnected datasets.
• Analyze business objectives and develop data solutions to meet customer needs.
• Demonstrated ability to effectively participate in multiple, concurrent projects.
• Improve and customize current data solutions to meet business functional and non-functional requirements.
• Research new and existing data sources in order to contribute to new development, improve data management processes, and make recommendations for data quality initiatives.
• Perform periodic data quality reviews for internal and external data.
• Ensure timely resolution of queries and data issues.
• Look for new ways to find and collect data by researching potential new sources of information.
• Work with data and analytics experts to strive for greater functionality in our data systems.

Key Skills:

• 3–5 years of experience in data engineering.
• Experience building and maintaining scalable data pipelines and data platforms.
• Strong proficiency in SQL and Python.
• Experience with ETL/ELT development and data ingestion and transformation frameworks.
• Understanding of Delta Lake/modern data storage formats and Medallion architecture (Bronze/Silver/Gold layers).
• Strong understanding of data transformations (cleaning, shaping, aggregating, and preparing data for downstream use).
• Data lineage (ability to track where data comes from, how it is transformed, and where it is consumed).
• Data quality and governance concepts.
• Experience supporting reporting and analytics (Power BI preferred).
• Familiarity with data security and access controls (RBAC).
• Microsoft Fabric experience (nice to have).
• Data catalog/lineage tools (Purview or similar) (nice to have).
• CI/CD (Azure DevOps, Git) (nice to have).
• Basic streaming or real-time ingestion exposure (nice to have).

Salary (Rate): £48,000 yearly

City: undetermined

Country: undetermined

Working Arrangements: remote

IR35 Status: undetermined

Seniority Level: undetermined

Industry: IT