Senior Data Engineer

About Ganit

Ganit Business Solutions is focused on turning data into practical business impact. The team blends scientific thinking, engineering craft, and analytical problem-solving to help organizations convert information into actionable insight and stronger decisions. Its culture emphasizes faster decision-making while reducing risk for enterprises that rely on data-driven strategies.

Role Overview

The Senior Data Engineer will take ownership of building and improving modern data pipelines, supporting cloud migration efforts, and creating scalable data solutions. This role also involves close collaboration with clients and internal teams to deliver reliable, governed, and production-ready data systems.

Responsibilities

• Build and maintain data pipelines using structured and semi-structured formats such as JSON, Parquet, CSV, and ORC, with support for both batch and streaming ingestion.
• Drive cloud migration initiatives and design Spark-based pipelines that can scale efficiently.
• Implement Medallion architecture patterns, including Bronze, Silver, and Gold layers, to support robust data processing.
• Tune and improve Spark code so migrations to cloud platforms run efficiently.
• Create and sustain data models while following strong governance standards.
• Set up cataloging approaches using Unity Catalog to help maintain dependable data quality.
• Lead the planning and implementation of Delta Live Tables (DLT) pipelines with an emphasis on secure and tamper-resistant data handling.
• Work directly with clients to improve cloud migration outcomes and ensure sound design and governance practices.

Experience and Technical Requirements

Candidates should have at least 5 years of practical experience in data engineering, including work on complex pipeline development and cloud migration programs. A bachelor’s degree or higher in Computer Science, Data Engineering, or a closely related discipline is expected. Strong working knowledge of Spark, SQL, Python, and other data processing tools is needed, along with solid experience in optimizing on-premises Spark code for cloud environments. Familiarity with Databricks, including Delta Live Tables, is important. Experience with AWS is expected, and exposure to Azure or GCP will be an added advantage. Excellent communication and teamwork skills are also required.

Eligibility

B.Tech / B.E. in any specialization. Applicants should also meet the experience requirement of at least 5 years in data engineering.

Additional Information

Preferred certifications include AWS, GCP, or Azure Data Engineer certifications.