Lead Data Engineer; Snowflake

Lead Data Engineer

Role

Summary:

We are seeking a highly skilled Lead Data Engineer to design, build, and scale modern data solutions within a cloud‑based environment, with a strong emphasis on Snowflake. The role combines hands‑on engineering excellence with technical leadership, guiding a small team of data engineers while delivering high‑quality, reliable, scalable, and AI‑ready data products. This individual will enable data‑driven decision‑making, advanced analytics, machine learning, and generative AI initiatives.

Data Engineering & Architecture:

• Design and build scalable data ingestion pipelines from structured and unstructured data sources into Snowflake.
• Develop and maintain ELT/ETL processes to transform, cleanse, and integrate enterprise data.
• Design reusable dimensional, semantic, and business‑ready data models that support analytics and AI use cases.
• Build and maintain consumable data products including curated datasets, data marts, semantic layers, APIs, and AI‑ready data assets.
• Design and implement enterprise data architectures that support scalability, interoperability, and future AI adoption.

AI‑Ready Data Platforms:

• Design and curate AI‑ready datasets that support machine learning, generative AI, intelligent agents, and advanced analytics.
• Implement metadata, lineage, and semantic modeling capabilities that improve data discoverability and AI readiness.
• Collaborate with AI and analytics teams to establish patterns for retrieval, search, knowledge management, and AI‑enabled business solutions.
• Evaluate and adopt emerging Snowflake capabilities, including Cortex AI, semantic models, vectorized data structures, and AI‑related platform services.

Data Products & Governance:

• Apply Data Product Management principles by establishing ownership, quality standards, service levels, and lifecycle management processes.
• Implement data quality monitoring, automated validation, observability, and governance frameworks.
• Ensure compliance with enterprise security, privacy, regulatory, and data governance requirements.
• Establish and maintain metadata standards, data lineage, business definitions, and cataloging practices.

Performance, Reliability & Fin Ops:

• Optimize Snowflake performance through query tuning, workload management, storage optimization, and architectural improvements.
• Ensure high availability, reliability, and scalability across data platforms and pipelines.
• Implement proactive monitoring, alerting, and observability practices.
• Drive cloud and Snowflake cost optimization through consumption monitoring, capacity planning, and engineering best practices.

Leadership & Delivery:

• Lead and mentor a team of 3–4 data engineers, providing technical leadership, coaching, and career development.
• Serve as the technical subject matter expert for Snowflake, modern data platforms, and AI‑ready data engineering practices.
• Define and enforce enterprise data engineering standards, architectural patterns, and development best practices.
• Collaborate with business stakeholders, product owners, analysts, architects, and data scientists to translate business objectives into scalable data solutions.

• Bachelor’s degree in computer science, Information Systems, Data Engineering, Software Engineering, or related technical field (or equivalent experience).
• 10+ years of experience in data engineering or related disciplines with increasing responsibility.
• Expert knowledge of Snowflake architecture, security, performance tuning, and workload management.
• Strong SQL, data modeling, and data architecture skills.
• Experience building enterprise‑scale ELT/ETL pipelines and data integration solutions.
• Experience with cloud platforms (AWS, Azure, or GCP).
• Proficiency in Python, Java, Scala, or similar modern programming languages.

• Snow Pro Core or Advanced Snowflake certifications.
• Experience designing enterprise‑scale Snowflake architectures.
• Experience supporting machine learning, generative AI, or agentic AI solutions through enterprise data platforms.
• Familiarity with Snowflake Cortex AI, semantic models, vector search, and AI‑ready data architecture.
• Experience working with structured and…