Senior Data Engineer

As a Senior Data Platform Engineer, you will be hands-on in building, operating, and improving our core data platform and AI/LLM enablement tooling. You'll focus on infrastructure, orchestration, CI/CD, and reusable frameworks that support analytics engineering and AI-driven use cases. You'll work closely with the Analytics Engineering and Insights teams and support other departments as they integrate with our data systems.

The core responsibilities for the job include the following:

Data Platform and Infrastructure:

• Build, deploy, and operate cloud infrastructure for data and AI workloads using Infrastructure as Code (Terraform).
• Provision and manage cloud resources across development, staging, and production environments.
• Develop and maintain CI/CD pipelines for data transformations, orchestration workflows, and platform services.
• Operate and scale containerized workloads on Kubernetes, including Airflow, internal APIs, and AI/LLM services.
• Troubleshoot and resolve infrastructure, pipeline, and orchestration failures to ensure platform reliability.
• Maintain and support existing ML services and pipelines to ensure stability and reliability (no expectation to design or develop new ML models or training pipelines).
• Continuously monitor and optimize platform performance and cost.

Framework, Tooling, and Enablement:

• Build and maintain reusable frameworks and patterns for dbt, Airflow, cloud data warehouses (Snowflake, BigQuery, Redshift, Databricks, etc. ), internal data, and AI APIs
• Build and support infrastructure and pipelines for AI/LLM-based use cases, including orchestration, integration, and serving.
• Improve developer experience for Analytics Engineering and Insights teams by reducing friction in local development, deployments, and production workflows.
• Create and maintain technical documentation and examples to support self-service analytics and data development.

Requirements:

• 5+ years of experience in data engineering, platform engineering, or similar hands-on roles.
• Strong programming skills in Python and SQL.
• Hands-on experience with: Terraform, Airflow, dbt, Kubernetes, Cloud platforms (AWS, Google Cloud, or Microsoft Azure), CI/CD pipelines (GitHub Actions, GitLab CI, CircleCI, etc. ), Cloud data warehouses (Snowflake, BigQuery, Redshift, Databricks, etc. ).
• Strong understanding of analytical data models and how analytics teams consume data.
• Experience integrating and operating LLM-based pipelines and services (not model training).

Soft Skills and Collaboration:

• Strong problem-solving skills and ability to debug complex platform issues.
• Strong preference for declarative development, with the ability to clearly separate what a system should do from how it is implemented.
• Clear communicator who can work effectively with both technical and non-technical stakeholders.
• Pragmatic, ownership-driven mindset with a focus on reliability and simplicity.