Data Architect / Principal Data Engineer III

Job Title: Data Architect / Principal Data Engineer III

Location: Farmington Hills, MI
Duration: Contract
Start Date: November 16, 2026
End Date: March 31, 2027
Domain: Wealth & Asset Management

Job Description

Position Summary

We are seeking an experienced Data Architect / Principal Data Engineer III to design, develop, and support scalable, secure, and high-performance enterprise data solutions within the Wealth & Asset Management domain.

The ideal candidate will have strong hands-on expertise in Python, SQL, PostgreSQL, AWS data services, data architecture, and ETL/ELT pipeline development. This role will focus on data ingestion, transformation, integration, data modeling, governance, and supporting AI-enabled data solutions across structured, semi-structured, and unstructured data sources.

Key Responsibilities

• Design, develop, and maintain scalable ETL/ELT pipelines and enterprise data-processing workflows.
• Architect data ingestion and transformation solutions for structured, semi-structured, and unstructured data.
• Develop reusable data-processing components using Python and SQL.
• Design and implement data models and database solutions using PostgreSQL, Amazon RDS, DynamoDB, and Amazon S3.
• Develop and support document ingestion and extraction solutions using Amazon Textract.
• Prepare and transform data for enterprise applications, search platforms, analytics, and AI/ML use cases.
• Implement vector-based data retrieval solutions using PostgreSQL and pgvector.
• Establish data quality, validation, reconciliation, metadata management, lineage, retention, and governance standards.
• Implement data security controls, encryption, and secure access management for sensitive enterprise data.
• Optimize database performance, data pipelines, scalability, reliability, and cloud infrastructure costs.
• Implement monitoring, troubleshoot data-processing issues, and ensure operational stability.
• Collaborate with application development, AI/ML, DevOps, enterprise architecture, cybersecurity, and business teams.

Required Qualifications

• 8+ years of experience in Data Engineering, Data Architecture, Data Integration, or related roles.
• Strong hands-on experience with Python and SQL.
• Extensive experience with PostgreSQL and Amazon RDS.
• Strong experience with AWS services, particularly DynamoDB and Amazon S3.
• Proven experience designing and developing ETL/ELT pipelines and data-processing workflows.
• Experience with data modeling, database architecture, and performance optimization.
• Hands-on experience working with APIs, JSON, and Parquet data formats.
• Experience with PostgreSQL vector extensions (pgvector) and vector-based retrieval.
• Strong understanding of data quality, metadata management, data governance, security, and monitoring.
• Experience working in large-scale enterprise or regulated environments.
• Experience supporting document processing, extraction, and AI-enabled data solutions.

Preferred Qualifications

• Experience in Wealth Management, Asset Management, Banking, or Financial Services.
• Experience with Amazon Textract and document extraction workflows.
• Experience supporting Generative AI, RAG, vector databases, and AI-powered applications.
• Knowledge of enterprise data architecture and cloud-based data engineering best practices.
• Experience implementing data lineage, auditability, encryption, and regulatory compliance controls.

Core Technical Skills

• Programming: Python, SQL
• Databases: PostgreSQL, Amazon RDS, DynamoDB
• AWS Services: Amazon S3, Amazon Textract
• Data Engineering: ETL/ELT, Data Ingestion, Data Transformation, Data Integration
• Data Formats & Integration: APIs, JSON, Parquet
• Vector Technology: pgvector, Vector Search, Retrieval
• Data Architecture: Data Modeling, Data Governance, Metadata, Data Quality, Data Lineage, Data Security
• AI-Enabled Data Solutions: Document Processing, Data Preparation for AI/ML, RAG
• Ideal Candidate Profile
• A senior-level Data Architect or Principal Data Engineer with strong hands-on Python, SQL, PostgreSQL, and AWS experience, capable of designing enterprise-grade data pipelines and supporting modern AI-enabled data platforms within a financial services environment.