Data Engineer – Data Platforms (GCP)
Classic Solutions · Haryana
- Company
- Classic Solutions
- Type
- Job
- Work mode
- On-site
- Location
- Haryana
- Salary / stipend
- ₹11 – 13 LPA
- Posted
- 30 Oct 2026
About this job
Experience: 5 – 7 Years
Required Skills
Google Cloud Platform (GCP), Python, SQL, PySpark, BigQuery, Cloud Composer (Apache Airflow), Dataproc, Pub/Sub, Cloud Storage, ETL/ELT, Batch & Streaming Pipelines, Data Warehousing, Data Modeling, Git, CI/CD
Job Summary
We are seeking an experienced Senior Data Engineer with strong Google Cloud Platform (GCP) expertise to design, develop, and maintain scalable, cloud-native data solutions. The ideal candidate should have strong hands-on experience in Python, SQL, PySpark, and GCP data services, with expertise in building enterprise-grade ETL/ELT pipelines and batch and streaming data processing solutions.
Key Responsibilities
- Design, develop, and maintain scalable ETL/ELT pipelines using Python and PySpark.
- Build and optimize cloud-native data solutions using Google Cloud Platform services.
- Develop and optimize SQL queries, data transformations, and data processing workflows in BigQuery.
- Design and manage workflow orchestration using Cloud Composer (Apache Airflow).
- Develop, optimize, and troubleshoot Spark applications running on Dataproc.
- Build event-driven data ingestion pipelines using Pub/Sub.
- Implement batch and real-time data processing pipelines for data warehouses and data lakes.
- Ensure data quality through validation, reconciliation, monitoring, and exception handling.
- Optimize pipeline performance, data processing, and storage efficiency.
- Implement data warehouse concepts, including star and snowflake schemas, fact and dimension modeling, SCD, partitioning, and clustering.
- Follow engineering best practices using Git/GitHub, CI/CD, and code reviews.
- Collaborate with Product Owners, Business SMEs, and Engineering teams to deliver reliable data products.
- Create and maintain technical documentation for data pipelines and architecture.
Mandatory Skills
- 5+ years of experience in Data Engineering.
- Strong hands-on experience in Python, SQL, and PySpark.
- Hands-on experience with Google Cloud Platform (GCP).
- Experience with BigQuery, Dataproc, Pub/Sub, and Cloud Composer (Apache Airflow).
- Experience developing production-grade ETL/ELT pipelines.
- Knowledge of batch and streaming data processing.
- Experience with data warehouse concepts and data modeling.
- Understanding of Git/GitHub and CI/CD practices.
Preferred Skills
- Google Dataflow and Apache Beam.
- Bigtable, Cloud Spanner, Cloud SQL, and AlloyDB.
- Google Cloud Storage and Cloud Scheduler.
- dbt, Apache Spark, Hadoop, and Spark/Scala.
- Docker, data governance, and data quality practices.
- Experience with enterprise-scale cloud migration initiatives.
- Familiarity with AI-assisted development tools such as GitHub Copilot.
Ideal Candidate: A Senior Data Engineer with strong GCP data platform expertise, capable of building and optimizing scalable batch and streaming pipelines, enterprise ETL/ELT solutions, and cloud-native data architectures.
Pay: ₹1,100,000.00 - ₹1,300,000.00 per year
Work Location: In person
Listed from the company's public job post; the company is responsible for it. Always apply on the official page and never pay to apply. How listings work