Data Engineer

Overview

We are looking for a highly skilled Data Engineer to join our team. We are seeking an expert in Python data engineering who can build and maintain our data infrastructure and also be able to develop user-friendly web interfaces for our existing Python codebase. The ideal candidate will be a proactive problem-solver, adept at bridging the gap between raw data and actionable insights through both custom applications and powerful Power BI dashboards.

Main responsibilities:

• Design, build, and optimize scalable ETL pipelines using Python and SQL Server Integration Services (SSIS)

• Develop and integrate functional and intuitive web-based user interfaces for our existing Python applications using frameworks like Django, FastAPI or similar

• Create, deploy, and manage insightful and interactive dashboards and reports using Power BI to meet diverse business needs

• Ensure performance, reliability, and data integrity across systems and dashboards.

• Document data workflows and monitor ETL pipelines

Key Requirements :

• Proven experience as a Data Engineer with a strong portfolio of successful data projects

• Expertise in Python for data engineering, including deep knowledge of libraries such as Pandas, NumPy, and SQLAlchemy

• Demonstrable experience developing web user interfaces with Python frameworks like Django or FastAPI

• Strong proficiency in Power BI dashboard development, including data modeling, DAX queries, and visualization best practices

• Solid experience with Microsoft SQL Server and SQL Server Integration Services

• Excellent communicator, must be able to explain technical jargon in layman terms

• Self-starter, flexible, can-do attitude, capable of multitasking, structured and works well within a team environment.

• Ability to work with minimal guidance or supervision in a time critical environment.

Preferred Skills – Not Mandatory:

• Exposure to Azure Synapse Analytics, Azure Data Factory, or other Azure data services

• Experience with cloud-based data architectures, data lakes, or big data platforms

• A strong background in data warehousing concepts and best practices (e.g., dimensional modeling, ETL/ELT patterns) is highly welcome.

• Understanding of OLAP cube development using SQL Serve Analysis Services (SSAS)

Job Types: Full-time, Permanent

Pay: From ₹1,000,000.00 per year

Benefits:

• Work from home

Schedule:

• Day shift
• Monday to Friday
• Morning shift

Work Location: Remote