Job Description
Seeking a Senior Data Engineer / Data Architect to design, build, and support scalable, secure data solutions for enterprise Wealth & Asset Management applications. Focuses on data ingestion, ETL/ELT pipelines, data modeling, transformation, storage, integration, data quality, and governance across structured and unstructured data sources.
The Data Architect / Principal Data Engineer III will play a critical role in designing, developing, and supporting secure, scalable, high-performance data platforms and integration solutions within an enterprise AWS environment.
This position requires a highly technical, hands-on engineer with strong architectural capabilities and extensive experience in Python, SQL, PostgreSQL, Amazon RDS, DynamoDB, Amazon S3, and ETL/ELT engineering.
The ideal candidate will combine advanced data engineering expertise with the ability to design reliable data architectures supporting traditional enterprise applications, analytics, document processing, and emerging AI-enabled capabilities.
The role involves working with structured, semi-structured, and unstructured data, developing reusable ingestion and transformation frameworks, implementing enterprise data governance controls, and enabling vector-based information retrieval using PostgreSQL and pgvector.
Successful candidates will demonstrate strong technical judgment, problem-solving capabilities, and experience delivering production-grade data solutions within large enterprise or regulated environments.
Job Responsibilities
Key Responsibilities
Data Architecture and Engineering
Design and implement scalable, secure, reliable data architectures for enterprise Wealth & Asset Management applications.
Develop and maintain high-performance data ingestion, transformation, and ETL/ELT workflows.
Design data solutions supporting structured, semi-structured, and unstructured information.
Develop reusable Python and SQL components that simplify data processing and integration across enterprise systems.
Evaluate architectural approaches and recommend appropriate data storage, integration, and processing technologies.
AWS Data Platform Development
Design, develop, and support data solutions leveraging Amazon RDS, PostgreSQL, DynamoDB, and Amazon S3.
Develop and optimize relational and NoSQL data models based on application requirements, access patterns, scalability, and performance considerations.
Build integrations with internal and external applications through APIs and enterprise data interfaces.
Implement efficient JSON and Parquet processing workflows.
Optimize database queries, storage strategies, and data pipelines for performance, reliability, and operating cost.
AI-Enabled Data Solutions
Support ingestion, transformation, and preparation of data used by AI-enabled enterprise applications.
Implement document-processing workflows involving structured and unstructured financial information.
Support document ingestion and text extraction using Amazon Textract, where applicable.
Develop and maintain PostgreSQL/pgvector integrations for embedding storage, similarity search, and vector-based retrieval.
Collaborate with AI and application engineering teams to make enterprise data accessible, reliable, and suitable for intelligent search and retrieval applications.
Data Quality, Security, and Governance
Implement data quality controls, including validation, completeness checks, duplicate detection, reconciliation, and exception handling.
Establish data lineage, metadata management, retention, and governance practices.
Ensure appropriate protection of sensitive financial and customer information.
Implement secure data access, encryption, and access-control mechanisms.
Support enterprise auditability, traceability, and data integrity requirements.
Production Engineering and Operational Excellence
Monitor data pipelines, databases, and integration processes to ensure reliability and availability.
Diagnose and resolve complex production data-processing and database performance problems.
Improve processing efficiency, resource utilization, scalability, and operational resilience.
Establish effective logging, monitoring, error handling, and recovery mechanisms.
Contribute to engineering standards, design reviews, documentation, and continuous improvement initiatives.
Collaboration and Technical Leadership
Collaborate with application developers, AI engineers, DevOps teams, enterprise architects, cybersecurity professionals, and business stakeholders.
Translate business and technical requirements into scalable, maintainable data solutions.
Provide technical guidance on data architecture, engineering practices, technology selection, and implementation approaches.
Participate in architectural reviews and help establish consistent approaches to enterprise data integration and governance.
Communicate technical decisions and tradeoffs clearly to engineering teams and stakeholders.
Numbers & Facts
| Location | Farmington Hills, MI |
| Job Type | Contractor |
| Industry | Computer/IT Services |
| Salary | $55–$62 Per Hour |
| Year Founded | 1997 |
| Headquarters | Princeton, New Jersey, US |
| Website | http://www.innovativeinfotech.com |
Qualifications
Experience Required: 8+ Years
Industry: Financial Services — Wealth & Asset Management
We are seeking an experienced Data Architect / Principal Data Engineer to help design and deliver modern, scalable data solutions for enterprise Wealth & Asset Management applications.
Must Have Skills
Must Have: - 8+ years of data engineering, data integration, or related experience. - Amazon RDS. - DynamoDB. - Amazon S3. - PostgreSQL. - Python. - SQL. - ETL/ELT pipelines and data-processing workflows. - Data modeling. - APIs and JSON. - Parquet. - pgvector. - Data quality, metadata, governance, and security. - Operational monitoring.
Technical Must-Haves
8+ years of professional experience in data engineering, data architecture, data integration, or closely related disciplines.
Python: Strong hands-on proficiency developing production-grade data-processing applications, automation, transformation logic, and reusable data engineering components.
SQL: Advanced SQL development skills, including complex queries, joins, window functions, query optimization, and performance tuning.
PostgreSQL: Extensive experience with relational database development, schema design, indexing, performance optimization, and production support.
Amazon RDS: Hands-on experience developing, configuring, integrating, and supporting AWS-managed relational databases.
Amazon DynamoDB: Experience with NoSQL data modeling, partition/sort key design, query patterns, indexing, and scalable database integration.
Amazon S3: Experience building cloud-based data ingestion, storage, and processing solutions using S3.
ETL/ELT Engineering: Proven experience designing, building, optimizing, and maintaining scalable data ingestion and transformation pipelines.
Data Modeling: Strong understanding of relational and NoSQL data modeling, schema design, normalization, and data architecture principles.
Data Integration and Formats: Experience integrating REST APIs and processing JSON and Parquet data.
PostgreSQL pgvector: Experience supporting vector embeddings, similarity search, and vector-based retrieval within PostgreSQL.
Additional Required Competencies
Strong understanding of data validation, reconciliation, data quality, metadata, lineage, governance, and retention.
Experience designing secure data-processing solutions involving sensitive or regulated information.
Knowledge of encryption, access controls, database security, and operational monitoring.
Experience supporting document-processing and AI-enabled data applications.
Experience delivering and supporting solutions in large enterprise or regulated environments.
Strong analytical, troubleshooting, communication, and cross-functional collaboration skills.
Preferred Qualifications
The following experience is advantageous but is not required:
Financial services, banking, Wealth Management, or Asset Management domain experience.
Amazon Textract and document extraction workflows.
Retrieval-Augmented Generation (RAG) architectures and AI-powered enterprise search solutions.
AWS IAM, KMS, CloudWatch, and secure cloud infrastructure practices.
Data pipeline orchestration, event-driven architectures, and workflow automation.
CI/CD and Infrastructure as Code experience supporting AWS data platforms.
Experience with high-volume financial transaction processing or regulatory data management.
Experience mentoring engineers or serving as a technical lead on enterprise data engineering initiatives.
What Success Looks Like
The successful candidate will be able to:
Independently design and deliver reliable, production-ready AWS data engineering solutions.
Demonstrate advanced hands-on expertise in Python, SQL, PostgreSQL, and AWS database services.
Develop scalable ETL/ELT pipelines with strong data-quality and recovery capabilities.
Make sound architectural decisions involving relational databases, NoSQL, object storage, and vector retrieval.
Support AI-enabled data processing without sacrificing enterprise security, governance, or operational reliability.
Take ownership of complex technical challenges from architecture through implementation and production support.
Collaborate effectively with business and technology stakeholders in a regulated enterprise environment.
About Company
Innovative Information Technologies, Inc. is a leading provider of information technology services and solutions. Our mission is to deliver high-quality technological solutions that enable companies to meet their business goals more effectively. With offices located in the US and India, we offer our clients an array of flexible, cost-effective solutions that range from staff supplementation through complete project outsourcing. We offer onsite, offsite and offshore delivery models that are tailored to the needs of our clients. Specializing in specific technological competencies, our solutions are intentionally designed to allow our clients to maximize the power of technology for the ongoing success of their business.
Skills
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