Big Data Specialist

12 hours ago

Bareilly, Uttar Pradesh, India beBeeData Full time ₹ 1,20,00,000 - ₹ 1,50,00,000
Big Data Specialist Job Description

This is a full-time role for an experienced specialist in data processing with one of our prominent clients.

The specialist will be responsible for designing, deploying, and managing large-scale data processes to integrate information 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 data pipelines using Informatica and other tools to process and transform big 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 scalable data solutions and automation 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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