Software Engineer - (Sr. Spark)

Accountabilities

• Design, develop, test, deploy, and operate end-to-end data processing systems that meet enterprise performance, scalability, and reliability requirements.

• Build and optimize big data solutions using Apache Spark, Spark SQL, and related technologies across databases, streaming platforms, and data warehouses.

• Apply object-oriented design principles and sound software engineering practices to develop maintainable, efficient, and scalable applications.

• Build and maintain enterprise data platforms, including data ingestion pipelines, data lakes, ETL processes, and data warehouses.

• Design and implement efficient production deployments for data engineering projects using cloud-native services and best practices.

• Identify opportunities to improve data processing performance, system reliability, operational efficiency, and deployment workflows.

• Track project progress using lean, efficient processes, proactively identify delivery blockers, and collaborate with team members to resolve issues.

• Lead and mentor engineering teams, provide technical guidance, and promote high standards of coding, debugging, testing, and delivery.

• Work closely with clients and stakeholders to understand business requirements, communicate technical solutions clearly, and ensure successful project outcomes.

• Contribute to multi-cloud data engineering initiatives and help deliver solutions tailored to different cloud environments and business domains.

Requirements:

• Strong experience in object-oriented design, software development, and implementation.

• Demonstrated experience designing, building, testing, deploying, and operating end-to-end data processing systems.

• Hands-on expertise with Apache Spark, Spark SQL, and associated big data technologies.

• Experience building enterprise data platforms covering data ingestion, data lakes, ETL pipelines, and data warehousing.

• Strong coding, debugging, troubleshooting, and performance optimization skills.

• Experience deploying and operating production-grade data engineering solutions using cloud-native services.

• Familiarity with multi-cloud deployments is an advantage.

• Experience leading technical teams, mentoring engineers, and coordinating delivery across project teams.

• Strong organizational skills, with the ability to track project progress, prioritize deliverables, identify risks, and resolve blockers proactively.

• Excellent communication and presentation skills, including the ability to explain technical concepts and engage effectively with clients.

• Knowledge of additional big data technologies such as Hadoop, HDFS, Hive, Impala, HBase, MongoDB, Cassandra, and Kafka is a plus.

• Domain knowledge in industries such as healthcare, banking and financial services (BFSI), or retail is an advantage.

• A collaborative, delivery-focused mindset, with the ability to balance technical excellence, team leadership, and business objectives.

Benefits:

• Full-time opportunity: Join a dedicated engineering team working on enterprise-scale data engineering projects.

• Multiple location options: Opportunities based in Ahmedabad, Hyderabad, or Vijayawada, India.

• Technical growth: Work with Apache Spark, Spark SQL, enterprise data platforms, and modern cloud technologies.

• Leadership opportunities: Apply your technical expertise while mentoring team members and contributing to engineering best practices.

• Enterprise-scale impact: Build and optimize data solutions that support complex business needs across multiple industries.

• Cloud and big data exposure: Gain experience working with cloud-native deployments, distributed data processing, and modern data engineering ecosystems.

• Cross-functional collaboration: Partner with technical teams and clients to solve challenging data problems and deliver measurable outcomes.