Senior Data Engineer

5+ years in Data Engineering, Software Engineering, or Distributed Systems roles. Proven experience building and operating data-intensive and streaming systems. Hands-on experience with Apache Kafka, Flink, Spark Streaming, Databricks & GCP. Strong understanding of event-driven architectures, CDC, and real-time data modeling. Proficiency in Python or PySpark, and solid command of SQL. Experience with cloud-native data services (GCP, Azure, or AWS) and workflow orchestration (Airflow/Composer). Strong understanding of data modeling and storage formats (Delta, Parquet, Avro). Experience with CI/CD for data pipelines, testing frameworks, and infrastructure automation (Terraform).

Design, implement, and optimize high-throughput, low-latency data pipelines. Build scalable data ingestion and transformation frameworks. Ensure fault-tolerance, exactly-once semantics, and replayability in event processing. Design data models across streaming, analytical, and serving layers. Partner with Data Architects to evolve domain-driven data models. Implement optimal partitioning, clustering, and indexing strategies. Embed observability, lineage, and data quality validations into pipelines. Define and enforce SLAs and SLOs for data delivery. Act as a senior engineer, mentor junior engineers, and contribute to design reviews.