Sr Data Engineer; MS Fabric

Overview

Experience:

8-12+ years (with deep hands-on delivery)

• Design and implement end-to-end data pipelines using Microsoft Fabric (Data Factory, Data Engineering, Lakehouse).
• Build and maintain Fabric Lakehouse architectures (Bronze/Silver/Gold) optimized for marketing and BI use cases.
• Implement incremental loads, CDC patterns, and data freshness strategies for large-scale analytical datasets.
• Optimize storage formats (Delta/Parquet), partitioning, and performance tuning in Fabric.
• Develop robust data transformation logic using:
  PySpark / Spark SQL, SQL-based transformations
• Perform data cleansing, standardization, enrichment, and deduplication across multiple marketing and customer data sources.
• Implement data quality checks, validation rules, and anomaly detection within pipelines.
• Maintain reusable transformation frameworks and shared data assets.

• Ingest and model data from marketing and customer platforms such as:
  Digital analytics (web, app, events), Campaign platforms (email, paid media, CRM, CDPs), Internal business systems (sales, finance, operations)
• Create conformed dimensions and fact tables for marketing performance, attribution, funnel analysis, and customer insights.
• Enable cross-channel reporting and identity-aware analytics.

• Design and optimize Power BI semantic models (datasets) for enterprise reporting.
• Build star schemas, calculation groups, and optimized DAX measures.
• Ensure report performance, scalability, and refresh reliability.
• Support self-service BI while enforcing enterprise data governance standards.
• Collaborate with analysts and business users on dashboard requirements and usability.

• Implement workspace strategies, environment separation (Dev/Test/Prod), and deployment pipelines in Fabric.
• Enforce data access controls, row-level security (RLS), and sensitivity labels.
• Establish monitoring, logging, and alerting for pipeline health and data reliability.
• Document data models, pipelines, and operational runbooks.
• Participate in on-call or production support rotations as needed.
• Influence data architecture decisions and analytics best practices.
• Work closely with product managers, marketing leaders, and BI teams to prioritize and deliver high-impact data products.
• Contribute to standards for data modeling, naming conventions, and pipeline design.

• 8+ years of experience in data engineering / analytics engineering roles.
• Strong hands-on expertise with Microsoft Fabric:
  Lakehouse, Data Factory, Data Engineering (Spark), Work spaces and deployment pipelines
• Advanced SQL skills and experience with large analytical datasets.
• Strong experience with Power BI:
  Semantic models, DAX, Performance optimization
• Proficiency in PySpark or Spark SQL.
• Deep understanding of:
  Data modeling (star/snowflake schemas), ETL / ELT design patterns, Incremental processing and CDC, Data quality and validation frameworks
• Experience operating data platforms in production environments.

• Experience supporting marketing analytics, customer analytics, or growth analytics.
• Comfortable working in agile, fast-moving environments with evolving requirements.
• Experience with enterprise marketing stacks (CDPs, CRM, campaign tools).
• Familiarity with data governance frameworks and privacy-aware data design.
• Experience migrating from legacy BI platforms to Microsoft Fabric.