Data Engineer IV - MS Fabric

The core responsibilities for the job include the following:

Data Architecture and Solution Design:

• Define architecture and technical direction for enterprise data platforms.
• Design scalable cloud-native lakehouse and data warehouse solutions.
• Lead complex technical design reviews and establish architecture standards.

Data Engineering and Platform Modernization:

• Architect high-volume batch and real-time/streaming pipelines.
• Define standards for ETL/ELT, data modeling, Delta Lake, and Medallion Architecture.
• Drive platform modernization, performance, scalability, and cost optimization.

Engineering Standards, Governance, and Reliability:

• Establish engineering standards for CI/CD, Infrastructure as Code, containers, and DevOps.
• Drive governance, data quality, lineage, security, and observability.
• Lead complex production issue resolution and performance optimization.

Technical Leadership and Mentoring:

• Mentor senior engineers and act as a technical SME for the data engineering organization.
• Partner with enterprise architects and business leadership on data strategy and execution.
• Lead technical discussions and influence engineering decisions across teams.

Technology Adoption and Innovation:

• Evaluate and contribute to adoption of modern data engineering technologies and architectural patterns.
• Contribute to cloud migration, platform modernization, and emerging technology initiatives.
• Promote engineering best practices that improve scalability, reliability, maintainability, and cost efficiency.

Requirements:

• Expert-level SQL, Python/PySpark, and Spark experience.
• Strong experience with Microsoft Fabric, Azure, and/or Databricks.
• Strong enterprise lakehouse/data warehouse architecture experience.
• Deep expertise in ETL/ELT and data modeling.
• Strong understanding of Delta Lake and Medallion Architecture.
• Experience architecting batch and real-time/streaming data solutions.
• Strong experience with CI/CD and DevOps.
• Experience with Infrastructure as Code.
• Strong understanding of data governance, quality, and lineage.
• Strong architecture and technical leadership experience.
• Excellent communication and stakeholder-management skills.
• Demonstrated ability to mentor senior engineers and technically lead engineering initiatives.
• Preferred / Additional Skills: Terraform, Kubernetes / Docker / OpenShift, Kafka / Event Hub / Flink, Snowflake / dbt, Apache Airflow, Data Governance / MDM / Lineage, REST / GraphQL / Enterprise Integrations, Generative AI / Agentic AI.