Data Engineer

Role Summary We are seeking a Lead Data Engineer with deep expertise in Snowflake and dbt to lead design, development, and delivery of modern data platforms. This role requires strong technical ownership, solution leadership, and the ability to guide teams in delivering high-quality, analytics-ready data solutions in a client-facing environment. Key Responsibilities Technical Leadership & Delivery Lead the architecture, design, and implementation of scalable data platforms using Snowflake and dbt Own end-to-end data engineering solutions , from ingestion to analytics-ready layers Define and enforce data engineering standards, best practices, and design patterns Drive Snowflake performance optimization, cost governance, and scalability strategies Design and govern dbt layered models (staging, intermediate, marts) aligned with analytics engineering best practices Team & Stakeholder Leadership Act as technical lead for project teams; mentor and guide junior and mid-level data engineers Perform design reviews, code reviews , and ensure adherence to quality standards Translate business requirements into technical designs and scalable data models Collaborate with stakeholders across analytics, BI, data science, and client leadership Support project planning, estimations, and risk management Data Operations & Governance Implement CI/CD pipelines for data workflows using Git-based version control and DevOps tools Drive data quality, testing, documentation, lineage, and observability using dbt and supporting tools Ensure compliance with security, access control, and data governance best practices Guide orchestration using Airflow, Azure Data Factory, or similar tools Required Skills & Qualifications Core Technical Skills 9 years of experience in Data Engineering , with at least 2 years in a technical lead role Strong hands-on expertise in Snowflake (architecture, optimization, streams, tasks, security, cost management) Deep experience with dbt (Core/Cloud) including macros, tests, seeds, snapshots, exposures, and documentation Advanced proficiency in SQL and complex query optimization Strong working knowledge of Python for data processing and automation Experience with cloud platforms (AWS / Azure / GCP) Experience with data orchestration frameworks Solid understanding of data warehousing, dimensional modeling, and analytics engineering principles Leadership & Soft Skills Proven ability to lead delivery and technical decision-making Strong client communication and stakeholder management skills Experience working in fast-paced, consulting-driven environments Ability to mentor teams and build high-performing data engineering practices Good to Have Experience with BI & visualization tools (Power BI, Tableau, Looker) Exposure to data governance, catalog, and metadata tools Experience with real-time or near-real-time data processing Prior experience leading enterprise-scale Snowflake implementations