Role & responsibilities :

- Experience Profile:

- 4-9 years of professional experience in data engineering, software development, or big data architecture.

- 3+ years of hands-on experience building solutions on Google Cloud Platform (GCP).

- Strong background in data modeling, database design, and end-to-end data pipeline development.

- Technical Expertise:

- Python: Proficient in using Python for data processing, scripting, and building custom data pipelines.

- SQL: Advanced SQL skills for complex data analysis, query tuning, and database optimization.

- Orchestration: Proven experience building, debugging, and managing complex DAGs in Apache Airflow (Cloud Composer).

- Transformation: Hands-on experience with dbt (data build tool) for managing transformation logic and quality testing.

- Modern Data Stack: Deep understanding of ELT/ETL patterns, data warehousing (BigQuery), and data lake architectures.

- GCP Proficiency:

- Experience with BigQuery, Dataflow (Apache Beam), and Cloud Storage.





- Familiarity with containerization and infrastructure management tools (e.g., Docker, Terraform).

- Experience with CI/CD implementation and version control systems (Git).

- Communication & Collaboration:

- Strong verbal and written communication skills with the ability to explain technical details to non-technical stakeholders.

- Self-motivated, detail-oriented, and able to work collaboratively in a fast-paced, client-facing workplace.

Preferred Skills:

- GCP Professional Certifications (e.g., Professional Data Engineer, Professional Cloud Architect).

- Experience in client-facing or consulting environments.

- Exposure to migrating legacy systems to modern cloud data platforms (e.g., migrations from on-prem or other clouds to GCP).

- Knowledge of data privacy regulations (GDPR, CCPA) and handling PII data within cloud environments.

📌 GCP Data Engineer with Dataflow, BigQuery, Pubsub, Dataproc (Spark) (Bengaluru)
🏢 PwC
📍 Bengaluru