Role Overview
As a Data Engineer , you will support data ingestion, transformation, ETL processes, and scalable data pipeline development across modern cloud and analytics environments. You will collaborate with business, analytics, and AI/ML teams to enable data-driven decision-making.
Responsibilities
- Design, develop, and maintain ETL / ELT data pipelines. Work with SQL databases, cloud data warehouses, and structured datasets. Extract, clean, transform, and load data from multiple sources. Support analytics-ready datasets and reporting requirements. Assist in schema design including star and snowflake schema concepts. Optimize SQL queries and improve database performance. Collaborate with Data Analysts, AI/ML Engineers, and business teams. Maintain documentation for pipelines, workflows, and data processes. Continuously learn modern data engineering and cloud technologies.
Skills Required
- Strong understanding of SQL, Joins, Query Optimization, and RDBMS concepts. Knowledge of ETL / ELT processes and Data Warehousing fundamentals. Understanding of Fact Tables, Dimension Tables, Star Schema, and Snowflake Schema. Basic to intermediate exposure in dbt is preferred. Exposure to cloud data warehouse concepts such as Snowflake, BigQuery, or Redshift is preferred. Basic knowledge of Python for data processing and automation. Exposure to Airflow, Databricks, PySpark, or similar tools is an added advantage. Good communication, documentation, and collaboration skills. Familiarity with AI/ML workflow support is a plus.
Education Requirements
BE / BTech / ME / MTech / MCA / MSc / BSc in Computer Science, IT, Data Science, Data Engineering, AI/ML, or related fields. Freshers with strong SQL, ETL, and Data Warehouse training are encouraged to apply. Relevant cloud or data engineering certifications are an added advantage.
Pay: ₹240,000.00 - ₹300,000.00 per year
Work Location: In person
