Fabric Data Engineer - Senior Associate

Responsibilities

• Developing and maintaining data pipelines that move, transform, and validate information across cloud and lakehouse environments
• Building scalable Fabric-based solutions for ingestion, orchestration, storage, and analytics use cases
• Applying data modeling, transformation, and performance tuning techniques to improve query speed and pipeline reliability
• Collaborating with client teams to gather technical requirements, interpret business needs, and translate them into engineering deliverables
• Monitoring pipeline health, troubleshooting failures, and resolving issues across data integration and warehouse workflows
• Using Azure Data Factory, Databricks, Apache Airflow, and Snowflake tools to support modern data platform delivery
• Reviewing code, schemas, and data structures to maintain consistency, security, and usable data outputs
• Mentoring junior team members on engineering methods, documentation, and delivery practices while managing assigned workstreams
• What You Must Have
• At least a Bachelor's degree
• At least 4 years of experience
• Oral and written proficiency in English required
• Designs and develops scalable data solutions in Microsoft Fabric. Works independently on modules and contributes to architecture discussions.
• Design and implement end-to-end data pipelines in Fabric
• Build and optimize Lakehouse architectures
• Develop advanced Power BI semantic models and reports
• Write and optimize complex SQL and PySpark transformations
• Integrate data from multiple sources (APIs, databases, streaming)
• Ensure data quality, governance, and security compliance
• Collaborate with business stakeholders for requirements
• Mentor junior team members
• Microsoft Fabric (Data Factory, Lakehouse, Warehouse)
• Power BI (DAX, modeling, performance tuning)
• SQL (advanced)
• Good knowledge of:
• PySpark / Spark
• Data modeling (star/snowflake schema)
• Azure services (ADLS, Synapse, etc.)
• Understanding of CI/CD and DevOps practices
• What Sets You Apart
• Preference for at least one of the following fields of study: Management Information Systems, Computer and Information Science, Systems Engineering, Electrical Engineering, Chemical Engineering, Industrial Engineering, Mathematics, Statistics, Mathematical Statistics
• Completing data engineering coursework or internships using Fabric, Azure, or Databricks
• Demonstrating SQL, Python, and data pipeline development for analytics solutions
• Analyzing data architecture, modeling, integration, and quality patterns for client deliverables
• Applying Agile ways of working while managing shifting workstream priorities
• Mentoring junior team members and reviewing deliverables for accuracy and clarity