About the role
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.