Senior Data Engineer

Your Responsibilities

• Lead the design and build of platform components that run across multiple clouds — addressing portability, cross-cloud replication, HA/DR, and data residency requirements of a regulated fintech environment, 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 modern open table formats such as Iceberg or Delta Lake.
• Own reliable, cost-aware operation of multi-cloud data infrastructure — 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.

Your Expertise

Our stack today: GCP · BigQuery · Kafka/Redpanda · Debezium · dbt · Spark · Airflow · Terraform · Kubernetes

• Preferably 6+ years of experience in data engineering or distributed backend systems, including 3**+ years operating large-scale streaming or data platform infrastructure in production**, and experience mentoring or technically leading engineers.
• Hands-on experience with streaming platforms (e.g., Kafka) and distributed processing tools (e.g., Spark or Flink) — our event streaming platform is built on Kafka.
• 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/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 — we run on BigQuery and looking to expand to other Cloud DWHs.

Who You Are

• A mentor and multiplier: passionate about driving engineering best practices and guiding a group of engineers to grow and deliver.
• An owner: you build it, you run it — comfortable carrying operational responsibility for mission-critical streaming and data systems.
• Comfortable with evolving scope and ambiguity as the platform grows from one cloud to many.
• Compliance-aware: you treat security, data residency, and auditability as first-class design constraints in fintech.
• Motivated by aligning data architecture with business outcomes, and by building platforms other teams love to use.

Nice to Have

• Familiarity with observability tools like Prometheus, Grafana, and Loki to monitor and troubleshoot data systems.
• Exposure to real-time OLAP engines like ClickHouse, Apache Druid, or Apache Pinot for low-latency analytics.
• 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.