Senior AWS Data Engineer
Confirmed on the employer's own hiring board on Oct 18, 2026. First seen by Alion on Jul 27, 2026. Persistent Systems scores B on the Alion truth index.
About Persistent
We are an AI-led, platform-driven Digital Engineering and Enterprise Modernization partner, combining deep technical expertise and industry experience to help our clients anticipate what's next. Our offerings and proven solutions create a unique competitive advantage for our clients by giving them the power to see beyond and rise above. We work with many industry-leading organizations across the world, including 20 Fortune 50 companies and 4 of the 5 top banks in both the US and India, and numerous innovators across the healthcare ecosystem.
Our disruptor's mindset, commitment to client success, and agility to thrive in the dynamic environment have enabled us to sustain our growth momentum. Persistent has been recognized across top industry platforms for innovation, leadership, and inclusion. We reported $1,654.4M FY26 revenue with 17.4% Y-o-Y growth. We have delivered 24 sequential quarters of growth with $436.0M in Q4 FY26 revenue, up 3.2% Q-o-Q and 16.2% Y-o-Y growth. Our 27,500+ global team members, located in 18 countries, have been instrumental in helping the market leaders transform their industries. We have been recognized as the Fastest Growing IT Services Brand Globally in the 2026 Brand Finance IT Services 25 Report. We named a Leader in the Everest Group Private Equity (PE) Services PEAK Matrix Assessment 2026 and Software Product Engineering PEAK Matrix Assessment 2026.
About Position:
We are seeking a skilled Senior AWS Data Engineer with 6-11 years of experience in building scalable, high-performance data solutions using AWS, Databricks, Python, PySpark, and SQL. The ideal candidate will be responsible for designing, developing, and optimizing cloud-native data pipelines that support analytics, reporting, and business intelligence initiatives. This role requires strong expertise in data engineering best practices, distributed data processing, cloud architecture, and data warehousing concepts. The candidate will work closely with architects, analysts, data scientists, and business stakeholders to deliver reliable, secure, and scalable data solutions across enterprise platforms.
- Role: Senior AWS Data Engineer
- Location: All Persistent Locations
- Experience: 6 to 11 years
- Job Type: Full-Time Employment
What You'll Do:
- Design, develop, and maintain scalable data pipelines using AWS, Databricks, PySpark, Python, and SQL.
- Build robust ETL/ELT solutions to ingest, transform, and load structured and unstructured data from diverse source systems.
- Develop and optimize large-scale data processing workflows using PySpark and Databricks.
- Create and maintain data models, curated datasets, data marts, and analytical layers for reporting and business intelligence.
- Leverage AWS services such as S3, Glue, Lambda, EMR, and Redshift to build cloud-native data platforms.
- Implement data quality checks, validation frameworks, monitoring processes, and automated reconciliation mechanisms.
- Optimize Spark jobs, SQL queries, and data pipelines for performance, scalability, and cost efficiency.
- Collaborate with business stakeholders, data scientists, analysts, architects, and application teams to understand requirements and deliver impactful solutions.
- Support data governance, metadata management, lineage tracking, and security compliance across enterprise data platforms.
- Troubleshoot pipeline failures, data quality issues, performance bottlenecks, and production incidents.
- Implement logging, monitoring, alerting, and operational support procedures for data platforms.
- Contribute to CI/CD implementation, deployment automation, and infrastructure reliability initiatives.
- Participate in architecture discussions, code reviews, and technical design activities.
- Create and maintain technical documentation, operational runbooks, and engineering standards.
Expertise You'll Bring:
- 6-11 years of experience in Data Engineering and Data Platform Development.
- Strong experience designing and building scalable batch and near real-time data pipelines.
- Hands-on expertise with ETL/ELT frameworks, data integration, and transformation techniques.
- Experience working with large-scale datasets and distributed computing platforms.
- Strong understanding of data engineering best practices, scalability, and reliability.
- Hands-on experience with AWS services including S3, Glue, Lambda, EMR, Redshift, IAM, CloudWatch, and SNS.
- Strong understanding of cloud-native architectures, security controls, monitoring, and cost optimization.
- Experience implementing enterprise data lake and analytics solutions on AWS.
- Knowledge of scalable cloud data platform design and architecture.
- Deep expertise in Databricks for enterprise-scale data engineering workloads.
- Strong proficiency in PySpark for distributed data processing and optimization.
- Experience with Delta Lake, Spark SQL, DataFrames, and Spark performance tuning.
- Strong understanding of distributed processing concepts and scalable analytics architectures.
- Advanced programming skills in Python for data processing, automation, orchestration, and pipeline development.
- Strong SQL expertise including complex query development, stored procedures, optimization, and analytical processing.
- Experience working with relational and cloud-based database platforms.
- Strong understanding of query performance tuning and database optimization.
- Knowledge of dimensional modeling techniques including Star Schema and Snowflake Schema.
- Strong understanding of data warehousing concepts and analytical data platforms.
- Experience creating curated datasets, semantic layers, and reporting models for business intelligence initiatives.
- Ability to design scalable data models supporting analytical and operational workloads.
- Experience with Git, CI/CD pipelines, Agile methodologies, and automation practices.
- Familiarity with monitoring, logging, and operational support processes.
- Experience implementing data quality frameworks, testing approaches, and platform reliability standards.
- Strong analytical, troubleshooting, and problem-solving capabilities.
- Ability to work effectively in fast-paced and collaborative environments.
Benefits:
- Competitive salary and benefits package
- Culture focused on talent development with quarterly growth opportunities and company-sponsored higher education and certifications
- Opportunity to work with cutting-edge technologies
- Employee engagement initiatives such as project parties, flexible work hours, and Long Service awards
- Annual health check-ups
- Insurance coverage: group term life, personal accident, and Mediclaim hospitalization for self, spouse, two children, and parents
Values-Driven, People-Centric & Inclusive Work Environment:
Persistent is dedicated to fostering diversity and inclusion in the workplace. We invite applications from all qualified individuals, including those with disabilities, and regardless of gender or gender preference. We welcome diverse candidates from all backgrounds.
- We support hybrid work and flexible hours to fit diverse lifestyles.
- Our office is accessibility-friendly, with ergonomic setups and assistive technologies to support employees with physical disabilities.
- If you are a person with disabilities and have specific requirements, please inform us during the application process or at any time during your employment
Let's unleash your full potential at Persistent -persistent.com/careers
“Persistent is an Equal Opportunity Employer and prohibits discrimination and harassment of any kind.”