HybridMidData Engineerposted 1mo ago

✦Role summaryAI-generated

The role involves designing, building, and maintaining SQL Server‑based data pipelines that ingest and transform data from internal systems and REST APIs. It is a hybrid position based in Grantham, requiring on‑site collaboration while offering flexible remote work.

Skills required

Microsoft sql server T-sql ETL Rest api integration Data pipelines Data modeling Python SQL ELT Data quality Data warehousing Data engineering Power BI CI/CD DevOps

About this role

We are seeking a Data Engineer with strong hands-on experience in Microsoft SQL Server, T-SQL, and data integration to design, build, and maintain reliable data pipelines and data solutions. The role will focus on ingesting data from internal systems and third-party platforms, including REST APIs, transforming and validating data, and delivering high-quality datasets for reporting, analytics, and operational use. This aligns with current SQL Server Data Engineer and integration-focused role patterns.

Working hours are: Monday to Thursday 08:00-16:30, and Friday 08:00 – 13:30. At least two days per week will need to be spent in the office at Grantham, as this is important for team collaboration and hands-on involvement with projects. The role will not be fully remote, and while we do offer a hybrid option for this role, Grantham is the primary base.

There will be a 2 stage interview process; initial interviews will take place via Teams, and will focus on technical ability and relevant experience. If successful at this stage, second interviews will take place on-site in person, with a view to having a tour of site, and meeting the team. This approach gives us a good balance between assessing technical skills and getting to you better in person.

Closing date for applications: Sunday 02nd August 2026.

Requirements

Key Roles and Responsibilities

Design, develop, and maintain SQL Server databases, tables, views, stored procedures, and ETL/ELT pipelines.

Write and optimize complex T-SQL queries for data extraction, transformation, reconciliation, and loading.

Build and support integrations with RESTful APIs, including data ingestion, pagination handling, authentication, and error handling.

Develop and maintain data interfaces between internal applications, external partners, and third-party systems.
Ensure data quality, consistency, integrity, security, and availability across pipelines and storage layers.
Troubleshoot pipeline failures, performance bottlenecks, schema changes, and data anomalies.
Create and maintain technical documentation including source-to-target mappings, transformation rules, API specifications, and operational runbooks.
Work with analysts, software engineers, product teams, and stakeholders to translate business requirements into scalable data solutions.
Support data warehouse, reporting, and BI initiatives by preparing curated datasets for downstream consumption.

Qualifications / Experience:

Bachelor’s degree in Computer Science, Data Engineering, Information Systems, or a related discipline, or equivalent practical experience (essential)
Proven experience in a Data Engineer, SQL Developer, Integration Engineer, or similar role (essential)
Advanced knowledge of T-SQL, including joins, CTEs, window functions, stored procedures, functions, and query optimization (essential)
Good understanding of JSON, XML, CSV, and other interchange formats (essential)
Strong understanding of performance tuning, indexing, execution plans, and database best practices (essential)
Ability to document solutions clearly and communicate with technical and non-technical stakeholders (essential)
Strong commercial experience with Microsoft SQL Server (essential)
Experience integrating data from APIs and external systems (essential)
Experience with data modelling, relational schema design, and data warehousing concepts (essential).
Experience with data validation, error logging, and reconciliation processes (essential)
Experience with Python for data engineering or automation.
Exposure to Power BI, SSRS, or other BI/reporting tools.
Familiarity with CI/CD, version control, and DevOps practices for data solutions.
Experience working with event-driven or near-real-time data ingestion.
Understanding of security models for APIs, including OAuth2, API keys, client ID/client secret, and token-based access.