AWS DMS Data Engineer for Real-time Ingestion & Pipelines

HCLTech; Seattle (WA); On-site; USD 78,000 - 148,000; Full time

Benefits offered by this job

Medical insurance

Dental & Vision

Life insurance

401(k) retirement plan

Paid time off

Job summary

HCLTech is seeking a Data Engineering professional with strong AWS DMS & CDC experience to drive data ingestion, real-time streaming, and scalable pipelines. The role requires Python/PySpark, AWS Glue, Kafka, and NoSQL knowledge, with on-prem and cloud integration.

This full-time position in Seattle involves collaborating with data teams, designing robust data architectures, and delivering near-real-time data access while leveraging modern cloud technologies for reliability and scalability.

Qualifications

• AWS DMS and CDC expertise required.
• Proficient in Python/PySpark for data processing.
• Experience designing scalable data pipelines across on-prem and AWS.
• Familiar with NoSQL databases (MongoDB, DynamoDB, Cassandra).
• Strong SQL and DB design skills.

Responsibilities

• Ingest data from multiple sources using Python and ETL tools.
• Design event-driven architecture using AWS EventBridge, Kafka, or SNS/SQS for real-time data streaming.
• Build and maintain scalable data pipelines across on-prem and AWS cloud.
• Develop Python scripts using pandas, NumPy for large datasets.
• Work with NoSQL DBs (MongoDB, Cassandra, DynamoDB) for storage and retrieval.
• Deploy applications in a cloud-native architecture with modern cloud tech.
• Monitor data workflows, troubleshoot, and optimize performance.
• Collaborate with data team on data ingestion, pipelines, and analytics needs.
• Document target data architecture, pipelines, and processing patterns.
• Identify opportunities for optimization and consolidation.

Skills

AWS DMS

AWS Glue

Kafka

SNS/SQS

Python/PySpark

Data lake

CloudWatch

CloudTrail

DB design SQL

NoSQL (MongoDB/DynamoDB)

Tools

AWS IAM

EKS

Job description

HCLTech is seeking a Data Engineering professional with strong AWS DMS & CDC experience to drive data ingestion, real-time streaming, and scalable pipelines. The role requires Python/PySpark, AWS Glue, Kafka, and NoSQL knowledge, with on-prem and cloud integration.

This full-time position in Seattle involves collaborating with data teams, designing robust data architectures, and delivering near-real-time data access while leveraging modern cloud technologies for reliability and scalability.