Offer summary

Qualifications:

4–8 years of experience in data engineering., Proficiency in SQL and Python., Experience with Spark, Airflow, Snowflake, and Azure Data Lake or similar technologies., Understanding of data modeling, version control, CI/CD, and data governance principles..

Key responsibilities:

Design and maintain scalable ETL/ELT data pipelines.

Apply data transformation, normalization, and enrichment rules.

Collaborate with cross-functional teams to align data structures with business needs.

Support data matching and entity resolution processes using AI/ML tools.

Job description

GT was founded in 2019 by a former Apple, Nest, and Google executive. GT’s mission is to connect the world’s best talent with product careers offered by high-growth companies in the UK, USA, Canada, Germany, and the Netherlands.

On behalf of the client, GT is looking for a Data Engineer.

About the Client & the Project

Our client is a leading global management consultancy known for tackling some of the world’s most complex business challenges. With a focus on strategy, transformation, and performance improvement, the firm partners with major organizations across industries to drive lasting impact. Recognized consistently as a top workplace, it combines deep industry expertise with a collaborative, innovative culture. Its centralized European hub plays a key role in supporting operations across the EMEA region, ensuring excellence and efficiency at scale.

About the Role

The Data Engineer will play a critical role in developing, maintaining, and scaling the pipelines and data systems that power BizMap’s unified data platform. Working alongside data architects, product managers, and analysts, this role is focused on ingesting, transforming, and enriching firmographic data from multiple third-party and proprietary sources.

It's a contract role for 6–12 months.

Responsibilities:

Build Data Pipelines: Design and maintain robust, scalable ETL/ELT pipelines to ingest and process third-party and first-party datasets.
Data Quality & Enrichment: Apply transformation, normalization, and enrichment rules to ensure data consistency and usability.
Collaborate Across Teams: Work with product managers, data architects, and content experts from Coro and Helix to align data structure with business needs.
Operationalize Matching & Merging Logic: Support the implementation of data matching and entity resolution processes using AI/ML tools and proprietary frameworks.
Monitor & Troubleshoot Pipelines: Build alerts, logs, and metrics to ensure data flows remain healthy and issues are identified and resolved quickly.
Documentation & Standards: Contribute to documentation, code quality standards, and internal best practices to ensure maintainability.

Essential knowledge, skills & experience:

Experience: 4–8 years in data engineering, with experience in building production-grade data pipelines.
Tech Stack: Proficient in SQL, Python, and experience with Spark, Airflow, Snowflake, and Azure Data Lake or similar technologies.
Cloud Platforms: Familiarity with Azure (preferred) or other major cloud platforms.
Data Engineering Best Practices: Understanding of data modeling, version control, CI/CD, and data governance principles.
Curiosity & Ownership: Proactive, detail-oriented, and eager to take ownership of projects and continuously improve systems.
Team Player: Comfortable working in a cross-functional environment and open to learning from and supporting teammates.

Interview Process

Interview with GT Recruiter
Client intro call
Technical Interview
Final Interview

Why join our client?

Join a fast-growing, high-impact team
Contribute to an ambitious effort to create the highest quality, most comprehensive business directory in the world.
Be part of a startup-style group within the company that’s redefining how they deliver consulting through productization and data innovation.
Work with cutting-edge data tools, including AI/ML enrichment, semantic matching, and modern cloud-based infrastructure.

Required profile