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# Sr Data Engineer

- **Company:** Hexaware Technologies
- **Location:** McLean, VA, United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Amazon Web Services, Amazon Elastic Compute Cloud, Amazon S3, ARM Architecture, Big Data, Code Review, Data Governance, Extract Transform Load (ETL), Amazon DynamoDB, Identity and Access Management, Information Retrieval, Job Scheduling, Python (Programming Language), Metadata Repositories, Performance Tuning, Power BI, Standard Sql, Search Technologies, Tableau (Software), Data Ingestion, Retrieval-Augmented Generation, Snowflake, Apache Spark, State Machines, Agentic-AI, Pyspark, AWS Glue, Tools for Reporting, Data Pipelines, Human in the Loop, AWS EKS, Control M
- **Published:** October 27, 2026
- **Apply:** https://www.dice.com/job-detail/b4a9e823-49d8-4a0c-8182-bdd7ae6ec8f5

## About the Role

* Strong hands-on experience with AWS EKS, EMR, EC2, Step Functions, DynamoDB, AWS Glue Data Catalog, S3, and IAM.
 * Advanced Snowflake development experience, including Iceberg Tables, Dynamic Tables, Views, Materialized Views, Tasks, Streams, governance, Horizon Catalog, Cortex, and Agents.
 * Expertise in PySpark, including containerized Spark workloads on EKS.
 * Experience with Snowpark for Python.
 * Hands-on experience with IICS for file-based ETL ingestion.
 * Strong SQL, data modeling, and performance-tuning skills.
 * Experience building RAG or Agentic AI proof-of-concept solutions.
 * Experience with Control-M job scheduling and orchestration.
 * Familiarity with reporting tools such as Power BI or Tableau.
 * Strong technical leadership, mentoring, and stakeholder communication skills.

## Description

We are looking for a Senior Data Engineer to lead the design and development of cloud-native data pipelines using AWS, Snowflake, IICS, and PySpark. The role involves leading Spark-on-EKS implementations, advanced Snowflake development, and AI/Agentic AI proof-of-concept initiatives while mentoring engineers and collaborating with stakeholders., * Architect end-to-end data pipelines using AWS, Snowflake, IICS, and PySpark.

 * Design and deploy containerized PySpark workloads on AWS EKS.
 * Build and optimize EMR clusters on EC2 or EKS for large-scale data processing.
 * Orchestrate workflows using AWS Step Functions and Control-M.
 * Manage metadata using AWS Glue Data Catalog and integrate with Snowflake Iceberg.
 * Use DynamoDB for pipeline state management, checkpoints, and configuration.
 * Lead the implementation of Snowflake capabilities, including Iceberg Tables, Dynamic Tables, Views, Materialized Views, Tasks, Streams, and data governance.
 * Work with Snowflake Horizon Catalog, Semantic Views, Cortex, Snowflake Agents, and token-usage optimization strategies.
 * Design and develop RAG and Agentic AI PoCs covering vector search, BM25 hybrid retrieval, evaluation frameworks, human-in-the-loop controls, and security.
 * Develop PySpark and Snowpark pipelines for data ingestion and transformation.
 * Lead IICS file-based ingestion design and implementation.
 * Conduct code reviews, optimize performance, and mentor engineers.