Title: Data Architect / Principal Data Engineer IIILocation: Farmington Hills Michigan 48331
Duration: 6+ Months
Must Have- Amazon RDS
- DynamoDB
- ETL/ELT pipelines and data-processing workflows
- Experience with data modeling, APIs, JSON, Parquet, and pgvector
- PostgreSQL
- Python
- S3
- SQL
Senior Data EngineerWealth & Asset Management
Position Summary
The Senior Data Engineer is responsible for designing, building, and supporting 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.
Key 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.
Required Qualifications- 8+ years of experience in data engineering, data integration, or related roles.
- Strong 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.
- Strong 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.