Python Spark SQL Data Engineer with AWS
Persistent Systems · Data_Int_ Taxation
Apply ↗Skills
["SQL""Python PySpark""Scala"]Technology stack
{}Description
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 looking for a highly skilled SQL Scala Spark AWS Data Engineer to design, develop, and maintain scalable data solutions that support enterprise data processing, analytics, and business intelligence initiatives. The ideal candidate will have strong expertise in Spark, Scala, AWS services, and advanced SQL development, with experience building high-volume batch and streaming data pipelines. Role: AWS Data Engineer Location: Pune Experience: 8 to 12 Years Job Type: Full Time Employment What You'll Do: Design, develop, and maintain scalable data pipelines for enterprise data platforms. Build and support batch and real-time streaming data processing solutions. Develop ETL/ELT processes for data ingestion, transformation, and deployment. Create and optimize Spark-based applications for large-scale data processing. Implement and maintain data quality, validation, and monitoring frameworks. Work with business and technical teams to understand data requirements and deliver effective solutions. Develop and optimize SQL queries for high-performance data processing. Build data integration solutions across multiple enterprise systems. Support cloud-based data engineering initiatives using AWS services. Troubleshoot and resolve data pipeline, performance, and processing issues. Continuously evaluate and improve data processes to enhance scalability and efficiency. Collaborate with cross-functional teams to support analytics and reporting requirements. Maintain technical documentation and support operational best practices. Expertise You'll Bring: 8 to 12 years of experience in Data Engineering and Big Data technologies. Strong understanding of Apache Spark architecture and ecosystem. In-depth knowledge of Spark DStreams and Spark Structured Streaming. Hands-on experience implementing and supporting batch and streaming pipelines. Strong proficiency in Scala programming. Advanced SQL expertise with extensive experience in query optimization. Strong hands-on experience with CTEs, Window Functions, Nested Queries, and complex SQL development. Experience building scalable data processing solutions using Spark and Scala. Strong knowledge of AWS cloud services. Hands-on experience with AWS EMR, S3, Lambda, EC2, and Athena. Understanding of distributed data processing and large-scale data architectures. Experience troubleshooting and optimizing Spark jobs and workloads. Knowledge of ETL/ELT frameworks and modern data engineering practices. Familiarity with Data Warehousing concepts and architectures. Understanding of Data Lake and Lakehouse environments. Experience working with Kafka for real-time data streaming is preferred. Exposure to Splunk and monitoring solutions is an added advantage. Strong analytical, debugging, and problem-solving skills. Excellent communication and collaboration abilities. Ability to work effectively in Agile and cross-functional delivery teams. Strong commitment to building scalable, reliable, and high-performance data solutions. 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.?
Requirements
["SQL", "Python PySpark", "Scala"]
Roles & responsibilities
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