Experience: 5 to 10 Years

Location: Gurgaon

About the Role

We are looking for a skilled Data Engineer to design and manage scalable, high-performance data pipelines on Google Cloud Platform (GCP). You will focus on processing clickstream data—especially from Google Analytics BigQuery exports—in large-scale eCommerce environments. The ideal candidate has a strong command of BigQuery, Airflow, and Python, and is comfortable handling massive datasets (100B+ rows).

Key Responsibilities

Pipeline Development: Build and maintain automated data pipelines using Airflow to process clickstream data efficiently.

BigQuery Optimization: Use BigQuery for data storage, transformation, and query performance tuning.

Data Integration: Integrate data from sources including Google Analytics BigQuery exports.

Automation & Monitoring: Automate workflows and implement monitoring to ensure pipeline reliability.

Data Quality: Ensure high data quality through robust validation, transformation, and aggregation techniques.

Collaboration: Work cross-functionally with data science, product, and business teams to support analytics needs.

Documentation & Best Practices:



Maintain clear technical documentation and promote GCP data engineering best practices.

Scalability: Architect solutions that scale with growing eCommerce clickstream data.

Required Skills & Qualifications

5+ years of experience in data engineering, ideally in eCommerce or analytics-heavy domains.

Robust expertise with Google Cloud Platform (GCP): BigQuery, Cloud Storage, Dataflow, Pub/Sub, Cloud Functions.

Deep knowledge of BigQuery performance features: partitioning, clustering, cost optimization.

Experience building pipelines with Apache Airflow.

Proficient in Python and SQL for data processing and pipeline orchestration.

Familiarity with clickstream data and Google Analytics BigQuery exports.

Demonstrated ability to manage and optimize data at scale (100B+ rows).

Strong problem-solving, analytical, and communication skills.

Preferred Qualifications:

Previous experience with eCommerce analytics and transactional datasets.

Familiarity with monitoring and alerting for pipelines (e.g., logging, retries, error handling).

- Understanding of cloud security practices including IAM, VPC, and data access controls.

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