Senior Data Engineering Specialist

2 weeks ago

Nagpur, Maharashtra, India beBeeData Full time ₹ 20,00,000 - ₹ 25,00,000
ETL Engineer Job Description

Role Summary:

This is a full-time role for an ETL Engineer with one of our renowned clients in Pune location. The ETL Engineer will be responsible for designing, deploying, and managing ETL processes to integrate data from various sources. Daily tasks include using ETL tools, performing data modeling, ensuring data quality, and providing analytical insights.

Key Responsibilities:

  • Design, develop, and maintain scalable ETL pipelines using Informatica and other tools to process and transform large datasets.
  • Work extensively with SQL to query, optimize, and manage data across systems.
  • Implement and optimize data models following data warehousing concepts (Star Schema, Snowflake Schema, Slowly Changing Dimensions, etc.).
  • Develop automated data solutions and scripts using Python.
  • Leverage GCP services (BigQuery, Cloud Storage, Dataflow, Pub/Sub, etc.) for data ingestion, transformation, and storage.
  • Collaborate with data analysts, data scientists, and business stakeholders to deliver reliable datasets and insights.
  • Monitor and troubleshoot data pipelines to ensure performance and data quality.
  • Document data workflows, processes, and standards.

Qualifications:

  • 3–5 years of hands-on experience as a Data Engineer or in a similar role.
  • Strong proficiency in SQL (query optimization, stored procedures, performance tuning).
  • Solid experience with ETL development using Informatica and strong knowledge of data warehousing concepts.
  • Proficient in Python programming for data processing and automation.
  • Practical experience working with GCP services, especially BigQuery.
  • Understanding of data governance, data quality, and performance best practices.
  • Strong problem-solving skills and the ability to work in a collaborative team environment.

Good to Have:

  • Exposure to MLOps pipelines or integration with machine learning models.
  • Knowledge of other cloud platforms (AWS/Azure) and their data engineering services.
  • Experience with CI/CD tools and containerization (Docker/Kubernetes).

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