Senior Data Engineer

Summary

The Senior Data Engineer will design, develop, and maintain scalable cloud-based data pipelines and products using Azure Databricks, PySpark, Python, and SQL. Working within an Agile DevOps team, the role focuses on building robust ETL/ELT processes and optimizing data platform architecture.

We are looking for a Senior Data Engineer to join an Agile Data Engineering team and help build and evolve a modern, cloud-based data platform. You will design, develop, and operate scalable data solutions that support critical business processes and enable data-driven decision-making.

Key Responsibilities

Senior Data Engineer - Cloud Data Platform

We are looking for a Senior Data Engineer to join an Agile Data Engineering team and help build and evolve a modern, cloud-based data platform. You will design, develop, and operate scalable data solutions that support critical business processes and enable data-driven decision-making.

Key Responsibilities

  • Design, develop, and maintain scalable data pipelines and data products using Azure Databricks, PySpark, Python, and SQL.

  • Build and optimize data ingestion, transformation, and storage solutions for analytics, reporting, and operational use cases.

  • Develop and support ETL/ELT processes integrating data from multiple sources into trusted and governed data platforms.

  • Design and review cloud-native solutions leveraging Azure Data Lake Storage (ADLS), Azure Functions, Databricks, and Apache Airflow.

  • Ensure data quality, reliability, scalability, monitoring, and operational excellence across the data ecosystem.

  • Implement and maintain source control, CI/CD pipelines, and deployment automation using Azure DevOps.

  • Collaborate with business and technical stakeholders to translate requirements into robust and sustainable solutions.

  • Enhance existing data products, optimize platform capabilities, and continuously improve engineering practices.

  • Troubleshoot and resolve complex production issues using strong analytical and problem-solving skills.

  • Contribute to data architecture, engineering standards, and best practices across the organization.

  • Promote innovation, knowledge sharing, and continuous improvement within the Data Engineering community.

  • Champion Agile, DevOps, and DataOps principles as part of a cross-functional Scrum team.

Working Environment

You will work as part of an Agile DevOps team within a Data Engineering organization, collaborating with colleagues across engineering and business functions to analyze, design, develop, test, deploy, and support secure, scalable, and future-proof data solutions.

Your Profile

You bring a strong engineering mindset, a passion for data, and a drive to continuously improve both technology and ways of working.

What We Are Looking For

  • 5+ years of experience in Data Engineering, preferably on cloud-based data platforms.

  • Strong hands‑on experience with Azure Databricks, including Unity Catalog and Databricks Asset Bundles (DAB).

  • Hands‑on experience with Apache Airflow, ADLS, and Azure Functions.

  • Strong proficiency in Python (OOP), PySpark, and SQL.

  • Solid understanding of Apache Spark performance tuning and large‑scale data processing.

  • Experience building and maintaining ETL/ELT pipelines and modern data integration solutions.

  • Experience with Git, CI/CD, and Azure DevOps.

  • Knowledge of data modelling techniques, including dimensional modelling.

  • Strong analytical, troubleshooting, and communication skills.

  • Experience working in Agile/Scrum and DevOps environments.

Nice to Have

  • Experience with monitoring, observability, logging, and data lineage.

  • Familiarity with Delta Lake, Iceberg, or other modern data lake technologies.

  • Knowledge of data governance, metadata management, and data quality frameworks.

  • Azure and/or Databricks certifications.

  • Experience in Financial Services or other highly regulated environments.

What You Can Expect

  • The opportunity to work on a modern cloud data platform at scale.

  • A collaborative Agile environment with strong engineering and data practices.

  • The opportunity to contribute to architecture, standards, and continuous improvement.

  • A role combining hands‑on engineering with opportunities to influence how data solutions are designed and delivered.

See also

Data Engineering jobs by country — openings, pay and top skills →

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