Big Data Dev/Spark Scala Engineer

Job DescriptionRole - Big Data Dev/Spark Scala EngineerExperience Required - 7+ YearsMust Have Technical/Functional Skills Experience with Apache Ozone and/or Ceph as storage backends for analytics workloads Experience implementing exactly once / at least once streaming semantics Strong background in Spark performance tuning (CPU, memory, I/O, shuffle) Experience supporting mission critical production systems with strict SLAs Familiarity with CI/CD pipelines and automated testing for data applications Experience designing observability for streaming systems (lag, throughput, backpressure)Technical Skills Languages: Scala, Python (PySpark), SQL Big Data: Apache Spark (Core, SQL, Structured Streaming) Streaming: Kafka Ingestion / Orchestration: Apache NiFi Storage: Apache Ozone, Ceph, object storage concepts OS & Tooling: Linux, Git, CI/CD, monitoring and logging toolsRoles & ResponsibilitiesKey Responsibilities Design, develop, and maintain large scale Spark applications using Scala and PySpark Build and operate streaming heavy data pipelines using Kafka and Spark Structured Streaming Implement stateful streaming patterns including windowing, watermarking, late data handling, and checkpointing Develop robust event replay and reprocessing workflows using Kafka offsets and partitions Build ingestion and routing flows using Apache NiFi, including Kafka based ingestion patterns Implement end to end ETL/ELT pipelines with strong emphasis on low latency, fault tolerance, and scalability Optimize Spark jobs through partitioning strategies, memory tuning, shuffle optimization, and efficient data formats Integrate Spark workloads with distributed object storage systems such as Apache Ozone and Ceph Ensure data quality, consistency, and auditability through validation, reconciliation, and metadata capture Collaborate with platform, infrastructure, and operations teams on production readiness and capacity planning Support production systems, including monitoring, incident analysis, and root cause resolution Contribute to reusable frameworks, coding standards, and engineering best practices Participate in architecture reviews, code reviews, and technical documentationRequired Qualifications Bachelor’s degree in Computer Sci ence, Engineering, or equivalent practical experience Strong hands on experience with Apache Spark in production environments Advanced proficiency in Scala and PySpark Solid understanding of distributed systems and data processing at scale Strong experience with Kafka based streaming architectures Hands on experience with Spark Structured Streaming Experience building batch and real time pipelines Hands on experience with Apache NiFi for data ingestion and flow management Strong SQL skills and experience working with structured and semi structured data Experience working with object storage or distributed storage platforms Proficiency with Linux, shell scripting, and Git based version controlBase Salary Range : $80,000 to $110,000 Per AnnumTCS Employee Benefits SummaryDiscretionary Annual Incentive.Comprehensive Medical Coverage: Medical & Health, Dental & Vision, Disability Planning & Insurance, Pet Insurance Plans.Family Support: Maternal & Parental Leaves.Insurance Options: Auto & Home Insurance, Identity Theft Protection.Convenience & Professional Growth: Commuter Benefits & Certification & Training Reimbursement.Time Off: Vacation, Time Off, Sick Leave & Holidays.Legal & Financial Assistance: Legal Assistance, 401K Plan, Performance Bonus, College Fund, Student Loan Refinancing.