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.