Lead Data Software Engineer

We are looking for an experienced Lead Data Software Engineer to design and build resilient, scalable data systems that support critical business decisions. You will develop and maintain robust data pipelines, manage ingestion from diverse source systems, and ensure data accuracy across complex environments. Working with modern technologies such as PySpark, Spark SQL, and Databricks, you will help deliver reliable and well-governed data solutions at scale. You will also contribute to engineering standards, code quality, and continuous improvements across the data platform. In this role, you will combine hands-on technical expertise with team leadership and close collaboration across departments. It is an opportunity to solve challenging data problems while making a lasting impact in a quality-focused, Agile environment.

• Design, build, and maintain scalable data pipelines that ensure reliable data flow across multiple systems.

• Develop and manage ingestion pipelines that collect and process data from diverse source systems.

• Write clean, maintainable, high-quality, and thoroughly tested code based on strong software engineering principles.

• Collaborate with cross-functional teams to understand business and data requirements and translate them into effective technical solutions.

• Monitor pipeline performance, identify potential issues proactively, and maintain system reliability.

• Participate in code reviews, uphold engineering quality standards, and share technical knowledge with team members.

• Investigate and resolve data quality issues to ensure the accuracy, consistency, and reliability of datasets.

• Contribute to the continuous improvement of data architecture, development practices, and engineering standards.

• Create and maintain technical documentation to support knowledge sharing, operational continuity, and onboarding.

• Participate in Agile ceremonies, including sprint planning and regular team meetings.

• Provide technical leadership and support the development team in delivering reliable data engineering solutions.

• At least 5 years of relevant professional experience.

• At least 1 year of experience leading and managing development teams.

• Strong experience with PySpark and Spark SQL for building and managing large-scale data processing workflows.

• Hands-on experience developing and managing Databricks Lakeflow pipelines and Jobs for data orchestration.

• Proficiency with Auto Loader and JDBC/CDC ingestion strategies, including experience integrating data from DB2 and SQL Server.

• Strong knowledge of Delta Lake and Unity Catalog for data storage, management, and governance.

• Experience implementing data quality controls and source reconciliation processes to ensure trustworthy data.

• Background writing unit tests with pytest to validate code quality and reliability.

• Working knowledge of Git and Databricks Asset Bundles for version control and deployment management.

• Upper-intermediate English proficiency or higher (B2).

• Experience participating in DataStage migration projects.

• Experience extracting and integrating data from Dynamics 365 or Dataverse.

• Databricks certification.