Accountabilities

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.

Requirements

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.

Benefits

Opportunity to work on international projects for leading global brands.

Collaboration with highly skilled and diverse teams across different locations.

Healthcare benefits.

Employee financial programs.

Paid time off and sick leave.

Upskilling, reskilling, and professional certification opportunities.

Unlimited access to LinkedIn Learning, including more than 22,000 courses.

Global career development opportunities.

Volunteer and community involvement initiatives.

Employee Groups and opportunities to connect with colleagues.

An award-winning workplace culture recognized by Glassdoor, Newsweek, and LinkedIn.

How Jobgether works

We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.

We appreciate your interest and wish you the best!

Why Apply Through Jobgether?

Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.

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