Description

Build and optimize data pipelines, structures, and analytics layers to support reliable, large-scale data processing and delivery.

This role is hybrid.

Responsibilities

• Design, build, and optimize data pipelines and structures for reliable, efficient data processing at scale.
• Migrate and modernize pipelines to standardized, reusable ingestion patterns and layered data architecture.
• Contribute to the semantic and analytics layer, including dimensional modeling for reporting.
• Perform root cause analysis on data and process issues, diagnose problems, and validate outcomes.
• Engage with business teams to understand requirements, manage stakeholder expectations, and coordinate technical changes.

Required Skills

• Strong SQL, including performance tuning and optimization in large-scale analytical environments.
• Experience designing and building data pipelines and data lakes in a cloud environment.
• Proficiency in Python or Scala for pipeline development.
• Ability to perform root cause analysis and trace problems across systems.
• Experience managing stakeholder expectations across technical and business teams.
• Bachelor's degree or equivalent combination of education and experience.

Preferred Skills

• Familiarity with Microsoft Fabric, Databricks, and the Azure data stack, including Azure Data Lake Storage.
• Knowledge of dimensional modeling, star schema design, medallion architecture, and semantic layer concepts.
• Experience using AI tools, agents, or automation to accelerate engineering workflows.

Key Skills

Education

Any Graduate