Data Engineering & DevOps Principal

Core Responsibilities

• Pipeline & DataOps: Build and optimize scalable ETL/ELT pipelines and automated CI/CD workflows for data assets, AI integrations, and ERP system updates.
• Platform Administration: Oversee the data platform, driving cost efficiency, system reliability, and secure-by-design data governance practices.
• Collaboration & Support: Partner with data scientists, vendors, and business units to deliver data solutions; provide BAU support and track platform KPIs.
• Innovation: Utilize generative AI tools to accelerate development cycles and share DataOps best practices with the broader team.

Requirements

• Education: Degree in Computer Science, IT, Data Science, or related field.
• Experience: 10+ years in Data Engineering, DataOps and DevOps (Preferrable in Microsoft Data Stack)
• Technical Skills: * Strong expertise in cloud data platforms (ideally Spark/Databricks ecosystems) and unified data governance frameworks.
• Proficient in Python, SQL, Shell Scripting, Infrastructure-as-Code, and Git/DevOps automation.
• Experience with containerization (Kubernetes/Helm) and AI productivity tools (e.g., Copilot) is a plus.
• Soft Skills: Strong ownership, proactive problem-solving, and excellent communication skills for diverse stakeholder groups.