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Data Engineer | NDA

Role overview

Qualifications

  • 4–8 years in data engineering
  • Proficient in SQL, Python, and dbt
  • Experience in building production-grade data pipelines
  • Familiarity with Azure or other major cloud platforms

Responsibilities

  • Design and maintain robust, scalable ETL/ELT pipelines
  • Apply transformation, normalization, and enrichment rules to ensure data consistency
  • Collaborate with product managers and data architects to align data structure with business needs
  • Monitor and troubleshoot data pipelines to ensure data flows remain healthy

About the company

GT logo

GT

IT Services & IT Consulting

DevOps Support, Consulting and Outsourcing services for design and maintenance of your business IT infrastructure. We help our clients to deal with server maintenance, Linux configuration, virtualization and orchestration, monitoring, DBA, DNS, Email, CI/CD and cloud providers. We find the best solutions for IT companies and startups that operate a loaded infrastructure with high load on backed and databases. We are strong in the classic stack: Linux, Nginx, Apache, Netfilter/iptables, Email (Postfix, Exim), Backups, FreeBSD. Also we love all the most common systems for virtualization and orchestration: Docker, Kubernetes, OpenStack, KVM, Proxmox, VMware, Terraform, Ansible (and more, and more...) DBAs in our state are ready to help with various databases: MySQL, PostgreSQL, MongoDB, Redis, Oracle Database, Elasticsearch, Clickhouse. We are able to work with most of the largest cloud providers: AWS, Google Cloud, Azure, Digital Ocean, IBM Cloud, OCI, Heroku, Hetzner. We also gained vast experience in Git and CI/CD tools: GitLab, GitHub Actions, Bitbucket, Jenkins, TeamCity, Sonar, Sentry. We are not limited to all these technologies — we will always find a solution for your case. Feel free to contact us on Linkedin or email! Also welcome to visit our website for more details.

Company details

Company typeScaleup
IndustryIT Services & IT Consulting
Company size2 - 10

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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 who is interested in working with big data.

 

About the Client

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 Project & Role

The Data Engineer will play a critical role in developing, maintaining, and scaling the pipelines and data systems that power the client'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.

The engineer will support data operations across 2 ecosystems, contributing to the client's mission of building the best business directory in the world and enabling differentiated, data-driven insights for consultants and clients.

Contract duration: 6 months, with the possibility of extension.

 

Key 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 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.

  • dbt Development: Build and maintain data pipelines using dbt, developing models from raw data through staging and intermediate layers up to final semantic models for use in analytics and dashboards.

  • Documentation & Standards: Contribute to documentation, code quality standards, and internal best practices to ensure maintainability.

 

Ideal Candidate Profile

  • Experience: 4–8 years in data engineering, with experience in building production-grade data pipelines.

  • Tech Stack: Proficient in SQL, Python, and dbt, with strong experience in Snowflake. Additional experience with Spark, Airflow, 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.

 

Why Join Us?

  • Join a fast-growing, high-impact team at the intersection of 2 key projects, building a data product core to client’s future.

  • Contribute to an ambitious effort to create the highest quality, most comprehensive business directory in the world.

  • Be part of a project, a startup-style group within the company that’s redefining how we deliver consulting through productization and data innovation.

  • Work with cutting-edge data tools, including AI/ML enrichment, semantic matching, and modern cloud-based infrastructure.

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MR

Marcus Rivera

Chief Revenue Officer

m.rivera@company.com
linkedin.com/in/marcusrivera
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