Operating at the crossroads of financial services and advanced analytics, our client delivers cloud-native data platforms that unlock enterprise-scale insights and regulatory reporting. The organization champions Google Cloud innovation to modernize legacy warehouses and fuel AI-driven products.

Role & Responsibilities

Design, build and optimize petabyte-scale data marts on BigQuery for analytics and ML workloads.
Develop ELT pipelines with Dataflow, Apache Beam and Cloud Composer, ensuring end-to-end observability.
Implement partitioning, clustering and columnar compression strategies to reduce query cost and latency.
Orchestrate batch and streaming workflows integrating Pub/Sub, Cloud Storage and external databases.
Enforce data governance, lineage and security via IAM, DLP and encryption best practices.
Partner with product, BI and ML teams to translate business questions into performant SQL and repeatable templates.

Skills & Qualifications

Must-Have

4+ years data engineering on GCP.
Expert SQL and schema design in BigQuery.
Proficient Python or Java with Beam SDK.
Hands-on building Composer/Airflow DAGs.
ETL performance tuning and cost optimization.
Git, CI/CD and Terraform proficiency.

Preferred

Experience with Looker or Data Studio.
Familiarity with Kafka or Pub/Sub streaming patterns.
Data Quality tooling like Great Expectations.
Spark on Dataproc or Vertex AI exposure.
Professional Data Engineer certification.
BFSI analytics domain knowledge.

Benefits & Culture Highlights

Modern Bengaluru campus with on-site labs and wellness facilities.
Annual GCP certification sponsorship and dedicated learning budget.
Performance-linked bonus and accelerated career paths.

Skills: vertex ai,data studio,airflow,terraform,ci/cd,spark,beam sdk,bigquery,etl performance tuning,kafka,git,dataproc,data quality tooling,gcp,sql,schema design,java,cost optimization,etl,python,composer,looker,pub/sub

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GCP Data Engineer (BigQuery)