Senior Data Platform Engineer

We are currently looking for an experienced Senior Data Platform Engineer, with significant experience in building, scaling, and optimizing modern data platforms across public cloud environments.

We are located in the San Francisco Bay Area, but we are open to remote candidates for this role anywhere in the US.

Responsibilities:

• Lead the design, development, and operation of a scalable and secure data platform to support analytics, ML Ops, and business intelligence
• Collaborate closely with Data Science, Machine Learning, Application and DevOps teams to implement end-to-end ML Ops pipelines
• Architect and manage data warehousing solutions using Databricks, Dbt, and Spark
• Develop and maintain ETL/data pipelines that handle structured and unstructured data across diverse sources
• Optimize data storage, access, and processing for cost-efficiency and performance in GCP and AWS Cloud environments
• Build and maintain dashboards and analytics solutions using tools such as Sigma, Metabase, and other BI platforms
• Ensure compliance with data governance, security, and privacy best practices, including HIPAA, SOC-2, and other regulatory requirements
• Evaluate and integrate third-party anonymization and security solutions to protect sensitive data
• Provide strategic guidance on the evolution of the data platform to meet the company's growth and technical needs
• Design and implement scalable infrastructure for Large Language Model (LLM) operations, including training, fine-tuning, and inference workflows
• Collaborate with AI/ML teams to build and optimize LLM serving platforms for real-time and batch processing
• Develop monitoring and observability solutions for LLMs, ensuring model performance, cost-efficiency, and compliance with ethical AI guidelines
• Evaluate and integrate state-of-the-art LLM technologies into existing data platforms to enhance analytics and decision-making

Qualifications:

• Bachelor's or Master's Degree in Computer Science or equivalent experience
• 5+ years of industry experience in designing and building large-scale data platforms
• Strong expertise in SQL, Data Modeling, and Data Warehousing (Databricks, Snowflake, Redshift, BigQuery, etc.)
• Proficiency in writing Advanced SQLs and performance tuning
• Strong proficiency in Python for building, optimizing, automating and maintaining data pipelines and services
• Deep experience with Apache Spark and distributed data processing frameworks
• Hands-on experience with modern ETL/Orchestration frameworks such as Airflow, dbt, and others
• Knowledge of business intelligence tools such as Sigma, Metabase, Tableau, and Looker
• Strong familiarity with cloud-based infrastructure and managed data services in GCP and AWS Cloud
• Experience with CI/CD pipelines to automate testing, deployment and release of data engineering and analytics workflows using GitLab, GitHub etc
• Experience with tools like Kubernetes, Terraform, Pubsub, Debezium
• Exposure building data quality frameworks and automation
• Understanding of data governance, privacy, and regulatory frameworks (HIPAA, SOC-2, HITRUST)

Nice to Have:

• Experience working with ML Ops platforms and supporting Data Science teams
• Experience with ML Ops tools such as MLflow, Streamlit, and vector databases
• Familiarity with healthcare data standards (FHIR, HL7)
• Experience in real-time data processing and event-driven architectures
• Expertise in implementing data access controls and anonymization techniques

Salary and Benefits:

We offer competitive salary and benefits, including 401(k) matching, health, vision, and dental insurance, and very flexible paid time off.

The typical salary range for this role is $150,000 to $170,000 USD, depending on skills, qualifications, and relevant experience.