Data Engineer - AI/ML

Responsibilities

• Design, build, and optimize modern data platforms using technologies such as Databricks, Spark/PySpark, SQL, and cloud-based data services.
• Develop scalable data pipelines, orchestration frameworks, and reusable platform capabilities supporting analytics and data products.
• Help establish architecture standards, engineering patterns, governance, monitoring, reliability, and development best practices.
• Support the deployment and productionization of AI/ML workloads, including the infrastructure and processes required to scale, govern, monitor, and maintain them.
• Partner with engineering, analytics, AI/ML, and business teams to understand requirements and translate them into scalable technical solutions.
• Evaluate new technologies and capabilities that can expand the functionality and maturity of the data platform.

Qualifications

• Significant experience in senior-level Data Engineering, Data Platform Engineering, or similar roles.
• Strong hands-on experience with Databricks, Spark/PySpark, SQL, cloud data architecture, data pipelines, and orchestration.
• Demonstrated experience building or significantly enhancing modern data platforms.
• Exposure to MLOps, ML/AI production environments, or deploying and supporting machine learning workloads is strongly preferred.
• Strong understanding of software engineering practices, architecture, scalability, governance, observability, and platform reliability.
• Experience working in greenfield, transformation, or highly ambiguous technical environments.
• Strong communication and collaboration skills with the ability to work effectively across technical and business teams.
• Self-directed mindset with the ability to understand business objectives and independently determine appropriate technical solutions.