Senior Data Engineer

Overview

Senior Data Engineer to build and operate Tamara's multi-cloud data core, spanning event streaming, data warehousing and experimentation. The role is hands-on and includes technical leadership of 5-6 engineers.

What you'll do

• Lead the design and build of platform components that run across multiple clouds, addressing portability, cross-cloud replication, HA/DR and data residency, and designing against single-cloud lock-in.
• Build and operate large-scale event streaming infrastructure on Kafka, including configuration tuning and cross-cluster replication between cloud environments.
• Build and maintain real-time and batch data pipelines using tools like Kafka, Spark and Airflow.
• Drive the development of a scalable LakeHouse architecture using open table formats such as Iceberg or Delta Lake.
• Own reliable, cost-aware operation of multi-cloud data infrastructure, including SLO-based observability, data quality and lineage.
• Enable Analytics and Product teams through self-serve data products, well-modeled warehouse foundations and marts, and reusable ingestion (inbound) and consumption (outbound) patterns.
• Provide technical leadership to a group of 5-6 engineers and data engineers, leading design reviews, setting engineering standards, and driving knowledge sharing and documentation.

What you'll need

• Preferably 6+ years of experience in data engineering or distributed backend systems.
• 3+ years operating large-scale streaming or data platform infrastructure in production.
• Experience mentoring or technically leading engineers.
• Hands-on experience with streaming platforms (e.g., Kafka) and distributed processing tools (e.g., Spark or Flink).
• Hands-on experience building and operating data pipelines on GCP with BigQuery, and familiarity with multi-cloud patterns.
• Working knowledge of LakeHouse formats (Iceberg, Delta or Hudi) and columnar storage like Parquet.
• Experience with infrastructure-as-code and cloud-agnostic tooling (e.g., Terraform, Kubernetes) for deploying and operating data platforms across clouds.
• Strong in data modeling and optimizing cloud data warehouses.

Nice to have

• Familiarity with observability tools like Prometheus, Grafana and Loki.
• Exposure to real-time OLAP engines like ClickHouse, Apache Druid or Apache Pinot.
• Prior experience in fintech or a highly regulated industry, with awareness of data residency, security and compliance requirements.
• Experience in Airflow or similar orchestration platforms.

Details

• Our stack today: GCP, BigQuery, Kafka/Redpanda, Debezium, dbt, Spark, Airflow, Terraform, Kubernetes.
• Location: India.