Snowflake Data Engineer

Role: Snowflake Data Engineer

Location: Onsite, Michigan, USA (Locals Only)

Exp: 10+ Years

 Job Overview

We are looking for an experienced Data Engineer / Technical Lead with mandatory expertise in Snowflake, DataStage, and dbt (data build tool), along with strong skills in Data Warehousing, Data Modeling, and Data Engineering.

The ideal candidate will have hands-on experience with AWS data services, including Aurora, RDS, DMS, and DynamoDB, as well as Oracle, PL/SQL, and SQL. The candidate should also have leadership experience in customer-facing roles involving requirement gathering and solution design.

 Roles and Responsibilities

Technical Leadership and Data Engineering

• Lead end-to-end data warehousing projects using Snowflake, DataStage, and dbt, which are mandatory skills for this role.
• Design and implement scalable data models, ETL/ELT pipelines, and data architecture in Snowflake.
• Develop and optimize dbt models, transformations, and data workflows to support efficient analytics.
• Work with AWS data services, including Aurora, RDS, DMS, and DynamoDB, for data integration and migration.
• Optimize SQL and PL/SQL queries and improve database performance across platforms such as Oracle and PostgreSQL.
• Implement Change Data Capture (CDC) and real-time data-processing solutions.
• Ensure data governance, data quality, and adherence to data-engineering best practices.

Requirement Analysis and Customer Handling

• Collaborate with stakeholders to gather, analyze, and document business requirements.
• Handle Change Requests (CRs) and provide technical solutions aligned with business needs.
• Act as a bridge between business and technical teams to support data-driven decision-making.

Team Leadership and Mentorship

• Guide and mentor junior data engineers on Snowflake, dbt, and modern data-stack best practices.
• Ensure adherence to data security, compliance, and scalability principles.

Mandatory Skills and Experience

• 10+ years of hands-on experience in Data Engineering, Data Warehousing, and Data Modeling.
• Expert-level proficiency in Snowflake, DataStage, and dbt (data build tool). These are mandatory skills.
• Strong expertise in:
• AWS data services, including Aurora, RDS, DMS, and DynamoDB
• Oracle, PL/SQL, SQL, and database optimization
• ETL/ELT pipelines and data integration
• Data architecture and dimensional modelling, including Star Schema and Kimball methodology
• Experience in customer handling, requirement gathering, and solution design.
• Strong communication, stakeholder-management, and team-leadership skills.