Lead II - Data Engineering

Job Summary

5 to 8 years of Senior Software engineering experience, ideally in infrastructure or data platform roles. Proficiency in Python/PySpark and strong knowledge of SQL. Experience with Terraform or similar Infrastructure-as-Code (IaC) tools. Strong knowledge of at least one cloud platform (GCP/AWS) Solid CI/CD experience Data MLOps Expertise: Strong Background in Databricks, specifically Unity Catalog, medallion architecture, and Databricks Asset Bundles (DABs). Proficiency in Python and API frameworks such as FastAPI or Flask. Strong experience designing, developing, and maintaining RESTful APIs. Good understanding of data engineering concepts such as data modeling and workflow orchestration. Experience with MLOps and Data Engineering like having worked on Spark/Delta Lake/MLflow/ETL frameworks (e.g., Fivetran, Lakeflow Connect). Operational Excellence: Experience with Github workflows, including container versioning. Proficiency with incident management and observability tools (e.g., PagerDuty, system monitoring). Mindset Collaboration: An AI as a partner mindset. A collaborative approach, including asking questions, navigating unclear requirements, and actively contributing to knowledge sharing/community enablement.

Requirements

• 5 to 8 years of Senior Software engineering experience, ideally in infrastructure or data platform roles.
• Proficiency in Python/PySpark and strong knowledge of SQL.
• Experience with Terraform or similar Infrastructure-as-Code (IaC) tools.
• Strong knowledge of at least one cloud platform (GCP/AWS).
• Solid CI/CD experience.
• Data MLOps Expertise: Strong Background in Databricks, specifically Unity Catalog, medallion architecture, and Databricks Asset Bundles (DABs).
• Proficiency in Python and API frameworks such as FastAPI or Flask.
• Strong experience designing, developing, and maintaining RESTful APIs.
• Good understanding of data engineering concepts such as data modeling and workflow orchestration.
• Experience with MLOps and Data Engineering like having worked on Spark/Delta Lake/MLflow/ETL frameworks (e.g., Fivetran, Lakeflow Connect).
• Operational Excellence: Experience with Github workflows, including container versioning.
• Proficiency with incident management and observability tools (e.g., PagerDuty, system monitoring).
• Mindset Collaboration: An AI as a partner mindset. A collaborative approach, including asking questions, navigating unclear requirements, and actively contributing to knowledge sharing/community enablement.

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.