AWS PySpark Data Engineer: Scalable Data Pipelines

LTM; Irving (TX); On-site; USD 120,000 - 180,000; Full time

Benefits offered by this job

Medical plan

Disability coverage

401(k) match

Life insurance

Paid time off

Parental leave

Job summary

LTIMindtree in Irving, Texas seeks an AWS PySpark Developer to design, build, and optimize scalable data solutions on the AWS ecosystem. The role focuses on PySpark data processing, Iceberg/Hive data warehousing, and secure, cost-efficient pipelines.

You will deploy data solutions using S3, EMR, Glue, Athena, Lambda, and Redshift, while ensuring strong governance, performance, and collaboration with data scientists and engineers. This is a full-time, on-site position in the US.

Qualifications

• AWS certification(s) required or in progress.
• Hands-on with core AWS data services (S3, EC2, EMR, Glue, Athena, Lambda, Redshift, Kinesis).
• Strong PySpark data processing and open table formats like Iceberg.
• Experience with Hive-based data warehousing and data modeling.

Responsibilities

• Design, implement, and deploy scalable data solutions on AWS.
• Develop robust PySpark ETL/ELT pipelines for ingestion and loading.
• Build and optimize data pipelines using Iceberg and Hive formats.
• Design data warehousing schemas and optimize queries for analytics.
• Configure secure cloud infrastructure, including VPCs and security groups.
• Operate containerized workloads on EKS and manage Spark/Hive jobs.
• Tune performance and manage cost of big data applications on AWS.
• Implement data governance, security, and access controls in AWS.

Skills

AWS

PySpark

Data warehousing

Iceberg

Hive

ETL/ELT

Python

SQL

Boto3

Kubernetes

Tools

S3

EC2

EMR

Glue

Athena

Lambda

Redshift

Kinesis

Iceberg

Job description

LTIMindtree in Irving, Texas seeks an AWS PySpark Developer to design, build, and optimize scalable data solutions on the AWS ecosystem. The role focuses on PySpark data processing, Iceberg/Hive data warehousing, and secure, cost-efficient pipelines.

You will deploy data solutions using S3, EMR, Glue, Athena, Lambda, and Redshift, while ensuring strong governance, performance, and collaboration with data scientists and engineers. This is a full-time, on-site position in the US.