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# Senior Data Engineer

- **Company:** Robotics Technologies LLC
- **Location:** Sunnyvale, CA, United States
- **Experience:** Expert
- **Salary:** $166,400
- **Contract:** Temporary contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Airflow, Amazon Web Services, Amazon S3, Big Data, Cyber Security, Databases, Information Engineering, Data Integration, Extract Transform Load (ETL), Data Security, Data Systems, DevOps, Distributed Systems, Amazon DynamoDB, Identity and Access Management, JSON, Python (Programming Language), PostgreSQL, Metadata, Role-Based Access Control, Standard Sql, SQL Databases, Unstructured Data, Parquet, Data Processing, Data Ingestion, Apache Spark, Amazon Relational Database Service, Pgvector, Presto, Data Pipelines
- **Published:** November 8, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=a4f5c9999103f7bf

## About the Role

* 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:

 * Apache Spark
 * Trino (Presto)
 * Apache Airflow
 * AWS
 * SQL
 * Large-scale Data Engineering
 * Distributed Computing
 * AWS Knowledge- Does NOT need to be an AWS expert.

Should understand:

 * S3
 * IAM Roles
 * IAM Policies
 * RBAC / Permission

## Description

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., * 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.