Principal Data Engineer

• Lead the implementation of Snowflake solutions, including setting up Snowflake environments, schema design, warehouse setup, RBAC and ingestion and transformation data pipelines.
• Build scalable and maintainable ETL/ELT pipelines using tools and frameworks such as Azure Data Factory (ADF), Airflow / Dagster, and dbt, with SQL and Python.
• Design and implement robust data integration pipelines to ingest, process, and unify structured and unstructured data from a variety of sources—including APIs, cloud storage systems, External websites, and relational/non-relational databases—using a modern medallion architecture (bronze, silver, gold layers) to ensure data quality, lineage, and accessibility across the organization.
• Lead efforts in migrating legacy data systems to a modern cloud-based stack centered on Snowflake.
• Own the end-to-end data lifecycle, from ingestion and transformation to reporting and governance.
• Collaborate with product, data science, and analytics teams to define data models that support analytical dashboards, reporting, experimentation, and AI/ML initiatives.
• Create and manage reports and dashboards using Power BI to provide actionable insights to the team and leadership.
• Drive performance tuning, cost optimization, and security enforcement within the Snowflake platform.
• Utilize SQL and Python for ETL, data manipulation, analysis, and process automation.
• Implement data quality, monitoring, and governance frameworks across the data pipeline.
• Ensure data security, privacy, and compliance with relevant regulations (e.g., GDPR, CCPA).
• Implement and manage Snowflake's security features, such as access controls, encryption, and data masking.
• Drive initiatives to automate and improve data operations, including testing, CI/CD deployment, and documentation.
• Provide technical leadership and mentorship to a growing team of data engineers.
• Participate in long-term strategic planning, providing technical insights and recommendations to support business growth.

• 8+ years of experience in data engineering, data warehousing, or cloud data architecture.
• 3+ years of hands-on experience with Snowflake, including architecture, performance tuning, and security.
• Expertise in Snowflake performance tuning, warehouse sizing, and cost optimization.
• Experience in building secure patient and prescription data marts with strong adherence to HIPAA and Safe Harbor compliance requirements.
• Advanced proficiency in SQL and data modeling (star, snowflake, 3NF, and/or Data Vault).
• Proven experience building ETL/ELT Orchestration tools like Azure Data Factory, Airflow / Dagster, Airbyte and dbt.
• Strong understanding of data warehousing concepts, data modeling techniques (Kimball, Data Vault 2.0), and architecture best practices.
• Experience with cloud platforms such as Azure, AWS or GCP (especially Snowflake integrations, storage and data services).
• Proficiency in SQL and Python or another scripting language used in data engineering.
• Understanding and hands on experience in enabling data privacy, governance, and compliance frameworks (HIPAA, GDPR, etc.).
• Experience with Data orchestration tools.
• Expertise in setting up CI/CD pipelines and DevOps for data projects (e.g. GIT, Terraform, etc.).
• Skilled in cost-effective cloud resource allocation and management.
• Strong testing capabilities (unit, integration, end to end).
• Strong understanding of OLTP Vs OLAP.
• 5+ years of experience with Power BI for data visualization and reporting.

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