Senior Data Engineer
Job ID#: 26-2233
Location: Hyderabad/Vijaywada India.
Who We Are:
Since our inception back in 2006, Navitas has grown to be an industry leader in the digital transformation space, and we’ve served as trusted advisors supporting our client base within the commercial, federal, and state and local markets.
What We Do:
At our very core, we’re a group of problem solvers providing our award-winning technology solutions to drive digital acceleration for our customers! With proven solutions, award-winning technologies, and a team of expert problem solvers, Navitas has consistently empowered customers to use technology as a competitive advantage and deliver cutting-edge transformative solutions.
Overview:
We are seeking an experienced Data Engineer with strong hands-on expertise in Amazon Redshift, SQL development, ETL/ELT pipelines, and production data engineering support.
The primary responsibility of this role is to develop, maintain, monitor, troubleshoot, and optimize our existing Amazon redshift data warehouse and associated data integration workflows. The engineer will ensure the reliability performance accuracy and timely execution of scheduled data pipelines supporting enterprise analytics and reporting.
The ideal candidate will have experience with complex SQL development, ETL process design, job scheduling, production monitoring, performance tuning, and troubleshooting. Familiarity with tableau and its underlying data dependencies is important.
As part of a broader data and AI platform modernization strategy the engineer will also participate in the phased migration of existing redshift workloads to Databricks. The successful candidates must demonstrate a willingness and ability to learn Databricks, Delta Lake, and modern data engineering practices.
Key Responsibilities
Production Monitoring, Troubleshooting, and Support
Monitor scheduled ETL jobs, Redshift workloads, data pipelines, and production data processing activities.
Proactively identify and resolve job failures, performance bottlenecks, data discrepancies, and scheduling issues
Rapidly diagnose, debug, and resolve production issues involving SQL, ETL workflows, and scheduled automation.
Perform root-cause analysis of recurring production incidents and implement permanent corrective solutions.
Monitor data pipeline execution, processing times, failures, and system performance to ensure operational reliability.
Develop and maintain monitoring scripts, automated alerts, and operational dashboards for production workflows.
Participate in rotational on-call production support to troubleshoot and resolve critical data processing issues.
Maintain operational documentation, incident resolution procedures, and production support runbooks.
Collaborate with infrastructure, analytics, and other IT teams to resolve production issues and maintain data availability.
Redshift and ETL/ELT Pipeline Design, Development, and Automation
Design, develop, deploy, and maintain data warehouse solutions using Amazon Redshift.
Perform SQL performance tuning, query optimization, and troubleshooting to improve data processing efficiency
Analyze existing data models, schemas, tables, and transformation logic to identify performance and reliability improvements.
Develop and maintain scalable ETL/ELT solutions supporting enterprise data integration and analytics.
Work with Amazon S3, Python, and other AWS data services to support data processing and integration requirements.
Develop and maintain Python scripts and SQL-based data transformation solutions.
Maintain scheduled data processing jobs, including job dependencies, execution sequences, and automated recovery mechanisms.
Improve existing ETL solutions through SQL optimization, automation, and reusable engineering practices.
Implement error handling, retry mechanisms, logging, and alerts to improve pipeline reliability.
Work with enterprise source systems, including PeopleSoft, D2L, Salesforce, and other structured data…