Tredence
GCP Data engineer with Python/Pyspark,Airflow,Dataproc expertise
Skills
1 month ago
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Important information
Contract type:
Permanent
Location:
Bengaluru, Karnataka, India
Work mode:
Onsite
Published on:
21 September 2026
What they need
Job Description: Senior GCP Data Engineer
Job Title: Senior Data Engineer - GCP & Big Data Architecture
Experience Level: 6 to 9 Years of overall IT experience (with 3+ years of dedicated GCP)
Location: Bangalore / Chennai / Pune / Gurgram / Kolkata / Hyderabad
Role Overview
We are looking for a highly skilled Senior GCP Data Engineer with 6 to 9 years of experience to design, build, and optimize our next-generation enterprise data platform. In this role, you will lead the development of robust, scalable batch and real-time data pipelines. You will be the subject matter expert for our big data infrastructure, translating complex business needs into clean, production-ready architectures leveraging GCP, Python, Airflow, Dataproc, and PySpark.
Key Responsibilities
- Data Pipeline Development: Design, build, and maintain enterprise-grade ETL/ELT pipelines using Python and PySpark to process massive, unstructured, and structured datasets
- Orchestration & Workflow Management: Author, schedule, and monitor complex Directed Acyclic Graphs (DAGs) using Apache Airflow (Google Cloud Composer) to orchestrate modern data workflows
- Big Data Processing: Architect and tune scalable distributed computing environments using GCP Dataproc (Hadoop/Spark clusters) to optimize large-scale batch processing
- Data Warehousing: Manage and optimize data schemas, indexing, partitioning, and cost-efficient querying inside Google BigQuery.
- Data Architecture: Implement and scale modern frameworks like the Medallion Architecture (Bronze, Silver, Gold layers) or data lakes ensuring high performance
Required Technical Skills & Qualifications
Core Technical Stack (Must Haves):
- Google Cloud Platform (GCP): In-depth, hands-on experience with core data components including BigQuery, Cloud Storage (GCS), Pub/Sub, and Cloud Functions.
- Programming Language: Expert proficiency in Python for general programming and data engineering tasks.
- Big Data Processing: Deep technical expertise in PySpark / Apache Spark for distributed processing, including performance tuning and configurations on GCP Dataproc.
- Orchestration: Extensive experience designing, writing, and debugging Apache Airflow / Cloud Composer DAGs.
- Advanced SQL: Superior skills in writing, optimizing, and tuning highly complex SQL queries and analytic functions.
Preferred / Good to Have Skills:
- An active Google Certified Professional Data Engineer certification
Required Skills
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