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Machine Learning Technologies, LLC seeks a Senior Data Engineer to design, build, and support scalable 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.
The candidate should have 8+ years of experience, hands-on Python/SQL, and expertise with PostgreSQL, Amazon RDS, DynamoDB, S3, and data-quality controls.
US Citizen, Green Card, H-1B, OPT-EAD, CPT, Other
Work Authorization: US Citizen, Green Card, OPT-EAD, CPT, H-1B, H4-EAD, Other
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.
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.
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.
Required Technical Skill:
Must Have:
We are an equal opportunity employer. All aspects of employment including the decision to hire, promote, discipline, or discharge, will be based on merit, competence, performance, and business needs. We do not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical condition, pregnancy, genetic information, gender, sexual orientation, gender identity or expression, national origin, citizenship/ immigration status, veteran status, or any other status protected under federal, state, or local law.