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IN_Manager_ Data Engineer GCP_Data and Analytics_Advisory_Bangalore

Pwc
Bengaluru, IND
Full-time
Mid · 3+ years experience
Onsite
Discovered 3 weeks ago
Python
Free

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Job Description & Summary

Why PWC

At PwC, you will be part of a vibrant community of solvers that leads with trust and creates distinctive outcomes for our clients and communities. This purpose-led and values-driven work, powered by technology in an environment that drives innovation, will enable you to make a tangible impact in the real world. We reward your contributions, support your wellbeing, and offer inclusive benefits, flexibility programmes and mentorship that will help you thrive in work and life. Together, we grow, learn, care, collaborate, and create a future of infinite experiences for each other. Learn more about us .

At PwC, we believe in providing equal employment opportunities, without any discrimination on the grounds of gender, ethnic background, age, disability, marital status, sexual orientation, pregnancy, gender identity or expression, religion or other beliefs, perceived differences and status protected by law. We strive to create an environment where each one of our people can bring their true selves and contribute to their personal growth and the firm’s growth. To enable this, we have zero tolerance for any discrimination and harassment based on the above considerations.

Job Description & Summary

We are seeking an experienced Data Engineer – GCP to design, build, and operate scalable, reliable, and cost-efficient data pipelines on Google Cloud Platform. The role involves hands-on development using BigQuery , Dataflow, Dataproc , Cloud Composer, Pub/Sub, Cloud Storage, Python, SQL, and related GCP -native services, along with close collaboration with analytics, AI/ML, architecture, and business teams .

Responsibilities

  • Design, build, and maintain end-to-end batch and streaming data pipelines on Google Cloud Platform
  • Develop scalable data processing solutions using BigQuery , Dataflow, Dataproc , Pub/Sub, and Cloud Storage
  • Build and optimize Cloud Composer / Airflow DAGs for orchestration, scheduling, retries , and dependency management
  • Ingest, transform, and curate large-scale structured, semi-structured, and streaming datasets
  • Develop reusable ETL/ELT frameworks using Python, SQL, Apache Beam, and Spark / PySpark where applicable
  • Implement BigQuery performance and cost optimization through partitioning, clustering, query tuning, and data model improvements
  • Ensure data quality, reliability, lineage, observability, governance, and operational readiness
  • Collaborate with data scientists, analysts, architects, and business teams to support analytics, reporting, and AI/ML workloads
  • Implement secure access patterns using IAM, service accounts, encryption, and enterprise compliance standards
  • Provide production support, troubleshoot pipeline failures, and resolve performance bottlenecks
  • Document technical designs, data flows, operational procedures, and runbooks
  • Mentor 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 concepts
  • Hands-on experience with Dataflow and Apache Beam for batch and streaming pipelines
  • Experience with Dataproc , Spark, or PySpark for distributed data processing
  • Experience with Cloud Composer / Airflow for orchestration and workflow management
  • Experience with Pub/Sub and Cloud Storage for ingestion and data lake patterns
  • Strong Python skills for data engineering, automation, and reusable pipeline development
  • Understanding of IAM, service accounts, networking basics, and secure data access on GCP
  • Experience with ETL/ELT patterns, data modeling, data quality, and production support
  • Experience working in Agile teams

Preferred skill sets

  • Experience with Dataplex , Data Catalog, and data governance capabilities
  • Exposure to Dataform , dbt , or similar analytics engineering frameworks
  • CI/CD experience for data pipelines using Cloud Build, GitHub Actions, Azure DevOps, or similar tools
  • Experience with BigQuery ML
  • Knowledge of Cloud Functions, Cloud Run, Workflows, or Cloud Scheduler
  • Google Cloud Professional Data Engineer certification

Years of experience required

5 to 10 years

Education qualification

  • Bachelor’s or Master’s degree in Computer Science, Engineering, or related field
  • Education (if blank, degree and/or field of study not specified)
  • Certifications (if blank, certifications not specified)

Optional Skills

  • Desired Languages (If blank, desired languages not specified)

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