Lead Data Engineer (Snowflake & dbt Specialist)
- Job Title: Lead Data Engineer (Senior Individual Contributor)
- Location: Onsite/Hybrid – Minneapolis, MN (Local Candidates Only)
- Client: Andersen Windows & Doors (via CTS)
- Request ID: 53829-1
Required Skills & Qualifications
- Platform Expertise: Expert-level proficiency in Snowflake and dbt (data build tool).
- Data Modeling: Advanced expertise in Dimensional Modeling and Data Vault methodologies.
- Engineering Foundation: Mastery of SQL and deep experience in building scalable ETL/ELT pipelines.
- Secondary Tools: Practical experience with Fivetran for automated data integration.
- Leadership: Proven ability to mentor junior engineers and lead through technical influence and thought leadership.
- Communication: Exceptional ability to bridge the gap between technical implementation and non-technical business strategy.
Role Overview
We are seeking a Lead Data Engineer to serve as a technical north star within our Technology & Data organization. This is a senior-level individual contributor role that demands a rare blend of Analytics Engineering and Data Engineering expertise. You will not have direct reports, but you will lead through technical influence—setting high standards for code quality, conducting rigorous peer reviews, and mentoring a team of engineers. Your primary mission is to design and maintain high-performance data architectures using Snowflake and dbt, ensuring our data solutions are scalable, resilient, and aligned with strategic business goals.
Technical Core & Responsibilities
Advanced Data Architecture
- Modeling Mastery: Lead the design and implementation of conceptual, logical, and physical data models. Expert-level proficiency in Dimensional (Star/Snowflake) and Data Vault modeling is required.
- Performance Optimization: Implement advanced partitioning and indexing strategies to ensure optimal query performance across massive datasets.
- Standard Setting: Establish and enforce SQL best practices and architectural patterns across the engineering organization.
Pipeline Orchestration & ELT
- Modern Data Stack: Architect and optimize end-to-end ETL/ELT pipelines leveraging dbt (data build tool) for transformations and Snowflake as the primary data warehouse.
- Data Ingestion: Utilize Fivetran for efficient data extraction from various source systems into the warehouse.
- Resiliency & Scale: Build automated orchestration workflows with robust dependency management, error handling, and alerting.
DevOps & Engineering Excellence
- Code Management: Maintain high standards for version control and collaborative development using Azure DevOps or GitHub.
- Observability: Implement comprehensive logging, metrics, and monitoring to ensure the health and reliability of critical data pipelines.
- Agile Leadership: Actively participate in sprint ceremonies, driving iterative improvements and ensuring the team meets its technical commitments.
Thanks,
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Aditya Jain | New York Technology Partners
120 Wood Avenue S | Suite 504 | Iselin NJ 08830
