Data Engineer

Design, develop, and maintain scalable and reliable data pipelines using modern cloud data platforms. Architect and implement real-time data streaming pipelines using Apache Kafka / Apache Flink / Spark Streaming Design event-driven architectures for high-throughput, low-latency data flows across distributed systems Build stateful and stateless Flink / Kafka jobs for complex event processing, windowed aggregations, and stream joins Contribute to data architecture and modeling discussions to enhance data platform scalability and performance. Contribute to CI/CD pipeline setup, containerized deployments, and infrastructure-as-code practices

About the Role - We are looking for an experienced Data Engineer with over 6 years of experience to design, build, and optimize event-driven architectures for high-throughput, low-latency data flows across distributed systems to deliver business insights. The ideal candidate has strong expertise in SQL, Python, Snowflake, and hands-on experience with Streaming ETL - any 1 of Flink, Kafka, Spark Streaming, Mandatory skill set for consideration - Python, SQL, Streaming ETL 6+ years of hands-on experience in data engineering, backend engineering, or distributed systems Deep understanding of ETL/ELT processes and data warehousing concepts. Snowflake: Proficiency in Snowflake data warehouse including architecture, data warehousing, security, and performance optimization will be an added plus

Proven expertise in Streaming ETL stack - Any one of - Flink / Kafka / Spark streaming across 2 or 3 projects :

Apache Kafka: production experience with topic design, consumer groups, offset management, Kafka Streams or Kafka Connect Apache Flink: experience building streaming jobs, managing checkpoints, windowed computations, and state backends Alternatives considered: Apache Spark Structured Streaming, AWS Kinesis, Google Dataflow / Apache Beam

Good hands-on experience with data pipeline orchestration tools (e.g., Airflow, Prefect, Dagster). Experience working with cloud platforms such as AWS, Azure, or Google Cloud Platform. Experience in NoSQL DB - MongoDB, Cassandra, DynamoDB will be an added advantage

Soft Skills: Strong analytical and problem-solving abilities Excellent communication skills with experience working in consulting or client-facing roles Strong attention to detail and commitment to data quality

Education & Certifications: Bachelors / Masters degree in Computer Science, Engineering, Mathematics, or related technical field AWS DE / Solution architect certifications is an added advantage