Lead Data Engineer: Snowflake + Azure Lakehouse

TECHNOLOGY PARTNERS INC; St. Louis (MO); On-site; USD 103,000 - 172,000; Full time

Job summary

Technology Partners is seeking a Principal Data Engineer to lead a modern Snowflake + Azure lakehouse data modernization for large-scale claims data. You will own architectural outcomes, drive design decisions, and mentor a team of engineers in a fast-paced, client-facing environment.

Responsibilities include delivering end-to-end data architectures, implementing Medallion patterns, real-time ingestion, governance, and observable pipelines with focus on reliability and business impact.

Qualifications

• 5+ years in data engineering with at least 2+ years in a technical lead or principal role.
• Deep hands-on Snowflake architecture and optimization experience.
• Strong SQL skills with complex transformations and performance tuning.
• Experience with dbt Core for modeling and testing.
• Proven ability to operate in client-facing consulting environments.

Responsibilities

• Lead design and implementation of end-to-end data architecture across Snowflake and Azure environments.
• Build and deliver multiple data-architecture patterns (Snowflake-native, hybrid Azure + Snowflake, event-driven ingestion).
• Implement Medallion Architecture with full lineage, governance, and promotion rules.
• Design real-time ingestion pipelines using Snowpipe and Event Grid.
• Develop scalable pipelines for high-volume ingestion using Snowpark (Python/Scala).
• Mentor engineering teams and manage technical risks and timelines.

Skills

Snowflake

Snowpark

Advanced SQL

dbt Core

Azure Cloud

Data Governance

Leadership

Client-facing

ETL Pipelines

Python/Scala

Education

Advanced degree in Computer Science or Data Engineering

Tools

Azure Data Factory

Snowpipe

Event Grid

ADLS Gen2

Notebook Workflows

Streamlit

Job description

Technology Partners is seeking a Principal Data Engineer to lead a modern Snowflake + Azure lakehouse data modernization for large-scale claims data. You will own architectural outcomes, drive design decisions, and mentor a team of engineers in a fast-paced, client-facing environment.

Responsibilities include delivering end-to-end data architectures, implementing Medallion patterns, real-time ingestion, governance, and observable pipelines with focus on reliability and business impact.