Job Description

Staff Data Engineer

🚀 About the Role

Are you ready to build and scale the data infrastructure for a mission-driven organization using cutting-edge AI and data solutions ? This Staff Data Engineer role is your chance to be at the forefront of designing and implementing high-performance, scalable data systems that power innovative AI-driven solutions.

Reporting directly to the Head of AI , you will play a foundational role in architecting data pipelines, optimizing performance, and ensuring regulatory compliance in a highly secure environment . This position is ideal for a hands-on technical leader who thrives in fast-paced, small-team environments and is passionate about leveraging data for real-world impact .

🔹 What You’ll Do

• Design Scalable Data Systems: Architect and maintain secure, efficient data pipelines for batch and real-time processing .
• Ensure Compliance: Implement HIPAA-compliant de-identification and data governance strategies for sensitive information.
• Enable AI/ML: Deliver clean, structured data for LLM prompting, model training, and analytics workflows .
• Enhance Data Logging: Build systems to capture and analyze key interactions for downstream processing.
• Optimize Performance: Design Snowflake schemas and optimize query performance for scalability and low latency .
• Provide Leadership: Mentor junior engineers and guide cross-functional teams on data engineering best practices .
• Monitor & Validate: Establish data quality frameworks , detect anomalies, and ensure system reliability .
• Drive Strategy: Define and execute a roadmap for scalable data infrastructure , supporting AI and recommendation systems .

🎯 What You Bring

✅ Must-Have Skills & Experience

• 8+ years of professional experience in data engineering , with a proven track record in designing and scaling robust data infrastructure .
• Expertise in data pipeline architecture , including real-time streaming (Kafka, Kinesis) and batch workflows .
• Hands-on experience with Snowflake, Redshift, BigQuery, or Aurora , including schema design and query optimization .
• Strong programming skills in Python and SQL / NoSQL databases.
• Deep knowledge of HIPAA compliance , data privacy, and de-identification techniques .
• Experience working with distributed data frameworks (Apache Spark, Hadoop, Flink).
• Cloud expertise (primarily AWS , but familiarity with Azure is a plus).
• Experience with containerization (Docker) and orchestration tools (Kubernetes) .

✨ Nice-to-Haves

• Experience with AI/ML workflows , including feature stores and preprocessing pipelines .
• Prior experience working in a startup or fast-paced environment .
• Knowledge of graph databases and search & recommendation systems .
• Ability to set up best practices for data engineering from concept to full deployment .
• Strong communication skills —able to translate complex technical concepts into real-world business impact.

🌟 Why This Role?

• High Impact & Ownership – Play a pivotal role in shaping data strategy and AI initiatives from the ground up.
• Mission-Driven Work – Build AI-powered solutions that make a real difference in people's lives .
• Collaborative Culture – Work alongside a talented leadership team that values innovation, creativity, and teamwork.
• Career Growth – Be at the forefront of AI and emerging data technologies , expanding your expertise in data engineering and machine learning .

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