Senior Data Engineer

Eliassen Group; Farmington Hills (MI); On-site; USD 83,000 - 107,000; Full time

Benefits offered by this job

Medical, Dental, Vision benefits

401k with company matching

Life insurance

Job summary

On-site in Farmington Hills, MI, Eliassen Group seeks a Senior Data Engineer to design, build, and support scalable data solutions for Wealth & Asset Management applications. You will focus on ingestion, transformation, storage, governance, and AI-ready data across structured and unstructured sources.

The role requires 8+ years in data engineering, hands-on Python/SQL work, and experience with PostgreSQL, AWS services, and ETL/ELT pipelines.

Qualifications

• 8+ years of experience in data engineering, data integration, or related roles.
• Hands-on experience with Python, SQL, PostgreSQL, Amazon RDS, DynamoDB, and S3.
• Experience developing and supporting ETL/ELT pipelines and data-processing workflows.
• Experience with data modeling, APIs, JSON, Parquet, and pgvector.
• Understanding of data quality, metadata, governance, security, and operational monitoring.
• Experience working within large enterprise or regulated environments.
• Experience supporting document-processing and AI-enabled data solutions.

Responsibilities

• Design and develop scalable data ingestion and ETL/ELT pipelines.
• Build solutions for structured, semi-structured, and unstructured data.
• Develop reusable data-processing and transformation components using Python and SQL.
• Design and support data models using PostgreSQL, Amazon RDS, DynamoDB, and Amazon S3.
• Support document ingestion and extraction using Amazon Textract, where applicable.
• Prepare and transform data for application, search, analytics, and AI-enabled use cases.
• Support vector-based retrieval using PostgreSQL/pgvector, where required.
• Implement data quality, validation, reconciliation, metadata, lineage, retention, and governance controls.
• Implement secure data access and encryption for sensitive information.
• Optimize data pipelines and databases for performance, reliability, scalability, and cost.
• Implement monitoring and troubleshoot data-processing and integration issues.
• Collaborate with application, AI, DevOps, architecture, cybersecurity, and business teams.

Skills

Python

SQL

PostgreSQL

Amazon RDS

DynamoDB

S3

ETL/ELT pipelines

data modeling

APIs

JSON

Parquet

pgvector

data quality

governance

security

monitoring

Job description

Description:

On-site in Farmington Hills, MI

Our client seeks a Senior Data Engineer to design, build, and support scalable and secure data solutions for enterprise Wealth & Asset Management applications. The role focuses on data ingestion, transformation, storage, integration, quality, governance, and processing across structured and unstructured data sources.

We can facilitate w2 and corp-to-corp consultants. For our w2 consultants, we offer a great benefits package that includes Medical, Dental, and Vision benefits, 401k with company matching, and life insurance.

Rate: $ to $78.00/hr. w2

Responsibilities:

• Design and develop scalable data ingestion and ETL/ELT pipelines.
• Build solutions for structured, semi-structured, and unstructured data.
• Develop reusable data-processing and transformation components using Python and SQL.
• Design and support data models using PostgreSQL, Amazon RDS, DynamoDB, and Amazon S3.
• Support document ingestion and extraction using Amazon Textract, where applicable.
• Prepare and transform data for application, search, analytics, and AI-enabled use cases.
• Support vector-based retrieval using PostgreSQL/pgvector, where required.
• Implement data quality, validation, reconciliation, metadata, lineage, retention, and governance controls.
• Implement secure data access and encryption for sensitive information.
• Optimize data pipelines and databases for performance, reliability, scalability, and cost.
• Implement monitoring and troubleshoot data-processing and integration issues.
• Collaborate with application, AI, DevOps, architecture, cybersecurity, and business teams.

Experience Requirements:

• 8+ years of experience in data engineering, data integration, or related roles.
• Hands-on experience with Python, SQL, PostgreSQL, Amazon RDS, DynamoDB, and S3.
• Experience developing and supporting ETL/ELT pipelines and data-processing workflows.
• Experience with data modeling, APIs, JSON, Parquet, and pgvector.
• Understanding of data quality, metadata, governance, security, and operational monitoring.
• Experience working within large enterprise or regulated environments.
• Experience supporting document-processing and AI-enabled data solutions.