Data Ingestion & Orchestration · Experience building batch and streaming ingestion pipelines using GCP-native services · Knowledge of Pub/Sub-based streaming architectures , event schema design, and versioning · Strong understanding of incremental ingestion and CDC patterns , including idempotency and deduplication · Hands-on experience with workflow orchestration tools (Cloud Composer / Airflow) · Ability to design robust error handling, replay, and backfill mechanisms Data Processing & Transformation · Experience developing scalable batch and streaming pipelines using Dataflow (Apache Beam) and/or Spark (Dataproc) · Strong proficiency in BigQuery SQL , including query optimization, partitioning, clustering, and cost control. About Position: Identity & Access Management (IAM) Data Modernization – migration of an on‑premises SQL data warehouse to a target‑state Data Lake on Google Cloud (GCP) , enabling metrics & reporting, advanced analytics, and GenAI use cases (natural language querying, accelerated summarization, cross‑domain trend analysis) leveraging PySpark‑based processing, cloud‑native DevOps CI/CD pipelines, and containerized deployments on OpenShift (OCP) to deliver scalable, secure, and high‑performance data solutions.