Senior Data Engineer

Lead design and development of a multi-cloud data platform including event streaming, data warehousing, and LakeHouse architectures with strong focus on scalability, portability, HA/DR, and regulatory compliance.

Build and operate petabyte-scale real-time and batch data pipelines using Kafka, Spark, Airflow, and manage cross-cloud data replication and observability with cost and reliability considerations.

Provide technical leadership to a team of 5-6 engineers, including mentoring, setting engineering standards, conducting design reviews, and driving knowledge sharing.

6+ years experience in data engineering or distributed backend systems, with at least 3 years operating large-scale streaming or data platform infrastructure in production and technical leadership experience.

Hands-on expertise with Kafka-based streaming platforms and distributed processing tools like Spark or Flink.

Experience building and operating data pipelines on GCP with BigQuery and familiarity with multi-cloud deployment patterns.

Working knowledge of LakeHouse table formats (Iceberg, Delta, Hudi), columnar storage (Parquet), and infrastructure-as-code tools like Terraform and Kubernetes for multi-cloud data platform operations.

Experienced data engineer with a platform mindset and operational ownership over mission-critical, regulated fintech streaming and data systems across multiple clouds.

Proven technical leader who mentors engineers, drives best practices, and effectively manages evolving platform scope and complexity.

Compliance-aware engineer skilled in designing data architectures that align with business needs while meeting fintech security, data residency, and auditability requirements.