23 hours ago
Bengaluru, IndiaSenior / Staff+
Responsibilities
- Design, develop, and maintain high-performance real-time data processing applications using Apache Flink.
- Develop in-flight transformation logic with Apache Flink, Kafka Streams, KSQLDB, and Kafka Single Message Transforms.
- Build scalable mapping frameworks that transform source-system data into harmonized enterprise data models.
- Implement complex event processing, enrichment, filtering, aggregation, and windowing for streaming workloads.
- Optimize streaming pipeline performance for low latency, high throughput, and efficient resource utilization.
- Handle late-arriving and out-of-order events through event-time processing, watermarks, checkpointing, and state management.
- Integrate streaming applications with Kafka, Schema Registry, APIs, and downstream analytical platforms.
- Implement error handling, retry mechanisms, dead-letter queues, and monitoring for streaming applications.
- Collaborate with architects, API teams, and business stakeholders on transformation rules and streaming integration patterns.
- Develop automated testing frameworks and CI/CD pipelines for streaming applications.
- Monitor production streaming jobs and troubleshoot performance, scalability, and reliability issues.
Requirements
- 6–10+ years of experience in data engineering with strong expertise in real-time streaming solutions.
- Hands-on enterprise-scale experience with Apache Flink.
- Strong knowledge of Apache Kafka, Kafka Streams, KSQLDB, Kafka Connect, and Single Message Transforms.
- Experience designing event-driven data architectures and real-time data integration pipelines.
- Understanding of event-time processing, watermarks, windowing, checkpointing, stateful stream processing, and fault tolerance.
- Experience developing data transformation and harmonization frameworks for enterprise data platforms.
- Proficiency in Java and/or Scala; Python knowledge is desirable.
- Experience with Avro, Protobuf, JSON, Schema Registry, and serialization techniques.
- Strong SQL skills and experience with large-scale structured and semi-structured datasets.
- Preferred experience with Azure, AWS, or GCP.
- Familiarity with Git, Docker, Kubernetes, and monitoring tools is advantageous.
- Preferred experience with Confluent Platform and enterprise Kafka deployments.
- Exposure to Databricks, Snowflake, or Delta Lake is preferred.
- Knowledge of CDC patterns, API integration, and enterprise integration architectures is preferred.
- A bachelor's degree in Computer Science, Data Science, or Statistics, or a master's degree in Data Science is listed among the qualifications.
- Relevant certifications include Certified Data Management Professional from Riversand and Databricks Certified Associate Developer for Apache Spark 3.0.
Benefits
- Hybrid work arrangement with flex-time scheduling in India.
- Regular employment with hands-on experience, mentorship, and learning opportunities.
- Opportunity to work on AI-powered transformation and enterprise technology initiatives.
- Values-driven environment emphasizing integrity, inclusion, innovation, and collaboration.
Tech Stack
Apache FlinkApache KafkaApache SparkAWSAzureDatabricksDockerGitGoogle Cloud PlatformJavaKubernetesPythonScalaSnowflakeSQLTerraform
Categories
Data Engineering
About Genpact
Genpact is a global professional services and technology firm that runs and transforms mission-critical operations for large enterprises through consulting, managed services, and AI- and analytics-driven platforms. It serves industries such as banking, insurance, healthcare, and manufacturing/supply chain, modernizing finance, risk, customer service, and back-office processes. Headquartered in New York and listed on the NYSE (G), Genpact originated within GE before becoming an independent public company.