Senior Data Engineering Specialist

5 days ago

Rajkot, Gujarat, India beBeeData Full time ₹ 10,00,000 - ₹ 15,00,000
Job Overview

This is a full-time role for an ETL Engineer with one of our renowned clients.

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

  • Data Pipeline Design: Develop, implement, and maintain scalable data pipelines using Informatica and other tools to process and transform large datasets.
  • Database Management: Work extensively with SQL to query, optimize, and manage data across systems.
  • Data Modeling: Implement and optimize data models following data warehousing concepts (Star Schema, Snowflake Schema, Slowly Changing Dimensions, etc.).
  • Automation and Scripting: Develop automation scripts using Python to streamline data processing and workflows.
  • Cloud Services Integration: Leverage GCP services (BigQuery, Cloud Storage, Dataflow, Pub/Sub, etc.) for data ingestion, transformation, and storage.
  • Collaboration and Communication: Collaborate with data analysts, data scientists, and business stakeholders to deliver reliable datasets and insights.
  • Pipeline Monitoring and Troubleshooting: Monitor and troubleshoot data pipelines to ensure performance and data quality.
  • Documentation and Standards: Document data workflows, processes, and standards.

Qualifications and Skills

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

Bonus Requirements

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

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