01Responsibilities
Design, build, and maintain end-to-end batch and streaming data pipelines on Google Cloud PlatformDevelop scalable data processing solutions using BigQuery, Dataflow, Dataproc, Pub/Sub, and Cloud StorageBuild and optimize Cloud Composer / Airflow DAGs for orchestration, scheduling, retries, and dependency managementIngest, transform, and curate large-scale structured, semi-structured, and streaming datasetsDevelop reusable ETL/ELT frameworks using Python, SQL, Apache Beam, and Spark / PySpark where applicableImplement BigQuery performance and cost optimization through partitioning, clustering, query tuning, and data model improvementsEnsure data quality, reliability, lineage, observability, governance, and operational readinessCollaborate with data scientists, analysts, architects, and business teams to support analytics, reporting, and AI/ML workloadsImplement secure access patterns using IAM, service accounts, encryption, and enterprise compliance standardsProvide production support, troubleshoot pipeline failures, and resolve performance bottlenecksDocument technical designs, data flows, operational procedures, and runbooksMentor junior engineers and contribute to engineering best practices for GCP data platforms
Mandatory skill sets:
4+ years of experience as a Data Engineer with strong hands-on Google Cloud Platform expertise
Strong experience with BigQuery, GoogleSQL / SQL, and data warehousing conceptsHands-on experience with Dataflow and Apache Beam for batch and streaming pipelinesExperience with Dataproc, Spark, or PySpark for distributed data processingExperience with Cloud Composer / Airflow for orchestration and workflow managementExperience with Pub/Sub and Cloud Storage for ingestion and data lake patternsStrong Python skills for data engineering, automation, and reusable pipeline developmentUnderstanding of IAM, service accounts, networking basics, and secure data access on GCPExperience with ETL/ELT patterns, data modeling, data quality, and production supportExperience working in Agile teams
Preferred skill sets:
Experience with Dataplex, Data Catalog, and data governance capabilities
Exposure to Dataform, dbt, or similar analytics engineering frameworksCI/CD experience for data pipelines using Cloud Build, GitHub Actions, Azure DevOps, or similar toolsExperience with BigQuery MLKnowledge of Cloud Functions, Cloud Run, Workflows, or Cloud SchedulerGoogle Cloud Professional Data Engineer certification
Years of experience required:
5 to 10 years
Education qualification:
Bachelors or Masters degree in Computer .
