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Role description
We are seeking a high-performing GCP Data Engineering Lead / Associate Manager with 4 to 9 years of overall experience to join our rapidly growing Data Engineering practice across our major India delivery hubs.
Job Title: GCP Data Engineering
Experience Level: 4 to 9 Years
Locations: Bangalore, Chennai, Pune, Gurugram, Kolkata, Hyderabad (Hybrid / Office-based as per company policy)
Employment Type: Full-time
Role Overview
This is a dynamic player-coach role designed for a technical powerhouse who wants to accelerate their career into engineering management. You will remain hands-on in architecting data platforms using GCP, SQL, Python, Airflow, and PySpark, while managing client delivery, mentoring junior engineers, and driving agile engineering practices across our delivery teams.
Key Responsibilities
Design, build, and optimize scalable enterprise ETL/ELT batch and real-time pipelines using Python, PySpark, and GCP Dataproc.
Oversee the scheduling, monitoring, and debugging of multi-stage data workflows using Apache Airflow / Google Cloud Composer.
Design cost-efficient data models, schemas, and partition strategies within Google BigQuery to ensure rapid analytical query execution.
Collaborate directly with client product owners, business analysts, and Tredence delivery managers to translate complex business problems into clear technical roadmaps and sprint backlogs.
Enforce production-grade standards including automated data quality checks, CI/CD pipelines, containerization (Docker/Kubernetes), and Infrastructure as Code (Terraform).
Required Technical Skills & Qualifications
Core Technical Stack (Must Haves):
4 to 9 years of dedicated experience in Data Engineering and Big Data platforms.
Proven track record of acting as a Technical Lead, Module Lead, or Scrum Master for a data delivery track.
Google Cloud Platform (GCP): Production-level expertise with core data services: BigQuery, Cloud Storage (GCS), Pub/Sub, Dataproc, and Cloud Functions.
Programming & Big Data: Advanced coding skills in Python and distributed data processing utilizing PySpark / Spark SQL.
Orchestration: Hands-on experience developing complex DAGs inside Apache Airflow / Cloud Composer.
Advanced SQL: Deep understanding of database internals, indexing, analytical functions, and query optimization.
Preferred / Good to Have:
Familiarity with streaming architectures using Apache Beam / Dataflow.
Experience with Terraform for cloud infrastructure automation.
An active Google Cloud Professional Data Engineer certification.
Soft Skills & Tredence Culture Fit
Growth Mindset: Ability to thrive in a fast-paced, high-growth analytics consulting environment.
Strong Communication: Articulate, empathetic communicator capable of managing both internal engineering expectations and client deliverables.
Problem-Solving: Highly analytical mindset with a strong bias for action and removing blockers for the team.
Work arrangement
No
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