Data Engineer

Smart IT Frame LLC; Detroit (MI); On-site; USD 130,000 - 170,000; Full time

Job summary

Smart IT Frame LLC is seeking an experienced Data Engineer to design, build and optimize scalable cloud data pipelines, data lakes and data warehouses for analytics, ML and AI initiatives. The role requires hands-on expertise with Snowflake and AWS services, Python, and data integration tools.

You will collaborate with business and technology teams, ensuring robust data governance, metadata management and secure data delivery.

Qualifications

• 10+ years of data engineering experience.
• Insurance business/data domain experience is a major plus.
• Design, build, and optimize scalable cloud data pipelines, data lakes, and data warehouse solutions.
• Strong hands-on experience with Snowflake, AWS (S3, Lambda, DynamoDB, AWS CLI), Python, dbt, Qlik Replicate, DataStage, and CP4D.
• Expertise in Data Vault modeling, data integration, ETL/ELT, data quality, cleansing, deduplication, and migration.
• Experience with API development, relational/NoSQL databases, Git, DevOps, and CI/CD.
• Strong understanding of data governance, metadata, lineage, security, and enterprise data management.
• Partner with business and technology teams to define requirements and deliver scalable data solutions.
• Provide technical leadership, mentoring, architecture guidance, and engineering standards.

Responsibilities

• Partner with business and technology teams to define requirements and deliver scalable data solutions.
• Provide technical leadership, mentoring, architecture guidance, and engineering standards.

Skills

Strong communication

Problem-solving

10+ years data engineering experience

Insurance domain experience

Tools

Snowflake

AWS S3

AWS CLI

Lambda

DynamoDB

dbt

Qlik Replicate

InfoSphere DataStage

CP4D

Python

Job description

Skillset: Snowflake, S3, AWS CLI, Lambda, and DynamoDB, dbt, Qlik Replicate, InfoSphere DataStage, and CP4D, Data Vault, Python

Job Description:

10+ years of data engineering experience with strong communication and problem-solving skills.

Insurance business/data domain experience is a major plus.

Design, build, and optimize scalable cloud data pipelines, data lakes, and data warehouse solutions supporting analytics, ML, and AI.

Strong hands‑on experience with Snowflake, AWS (S3, Lambda, DynamoDB, AWS CLI), Python, dbt, Qlik Replicate, DataStage, and CP4D.

Expertise in Data Vault modeling, data integration, ETL/ELT, data quality, cleansing, deduplication, and migration.

Experience with API development, relational/NoSQL databases, Git, DevOps, and CI/CD.

Strong understanding of data governance, metadata, lineage, security, and enterprise data management.

Partner with business and technology teams to define requirements and deliver scalable data solutions.

Provide technical leadership, mentoring, architecture guidance, and engineering standards.