The company is looking to enable AI-powered capabilities across its products by designing and operating reliable, scalable data pipelines on Databricks. This role will focus on Data Engineering with opportunities to explore and apply Generative AI and Machine Learning technologies responsibly at scale.
Requirements
- 5+ years in Data Engineering (or adjacent ML/Data roles) building production-grade data pipelines and platforms.
- Strong proficiency in Python, SQL, and PySpark; deep experience with Databricks and cloud data stacks (AWS or equivalent).
- Expertise in Delta Lake/S3-class storage, version control (Git), and CI/CD for data services.
- Experience building monitoring and dashboards for data or AI services (Grafana or similar).
- Exposure to AI/ML applications in production environments, including LLM or retrieval-augmented workflows.
- Hands-on experience with OpenAI Agent Builder / AgentBricks or comparable AI agent frameworks.
- Familiarity with MLflow for experiment and model lifecycle management.
Responsibilities
- Design, build, and optimize batch and streaming pipelines on Databricks (Spark, Delta Lake) for high-volume, mission-critical data.
- Implement robust data modeling, transformation, quality, and metadata practices (expectations, profiling, lineage).
- Ensure reliability and performance of data services with CI/CD, orchestration (e.g., Databricks Workflows/Airflow), and infrastructure-as-code.
- Build observability (logging, metrics, dashboards, alerting) for data and downstream AI services.
- Partner with security, platform, and product teams to strengthen data governance, access control, and cost optimization.
- Collaborate with engineers to deliver LLM- and AI-backed features using OpenAI Agent Builder / Agent Bricks (or similar) and OpenAI/Azure OpenAI APIs.
- Contribute to retrieval pipelines, vector store integrations, and model evaluation processes.
Other
- You focus on reliability, scalability, and measurable outcomes.
- You collaborate across product, platform, and security teams to deliver robust, production-ready data and AI solutions.
- You stay curious about new data and AI technologies and apply them thoughtfully to improve business outcomes.
