Description

Job Responsibilities include:

Design, develop, and maintain scalable data pipelines, ETL/ELT workflows, and data integration solutions using Azure data services and Databricks.

Build, optimize, and manage large-scale structured and unstructured datasets to support business intelligence, analytics, and operational reporting needs.

Develop and maintain SQL-based data models, transformations, and database solutions to ensure data accuracy, quality, and performance.

Implement and support workflow orchestration using Airflow/Astronomer for automated data processing and scheduling.

Collaborate with data analysts, business stakeholders, and engineering teams to gather requirements and deliver reliable data solutions.

Monitor, troubleshoot, and optimize data platform performance while driving continuous improvements in data architecture, governance, and operational efficiency.

Required Qualifications:

Bachelor’s degree in computer science, Information Technology, Data Engineering, Data Science, Software Engineering, or a related technical field.

8–10 years of experience in Data Engineering, Data Warehousing, Cloud Data Platforms, or Enterprise Data Management.

Strong expertise in SQL, Azure Data Services, Databricks, ETL/ELT development, data pipeline design, and workflow orchestration using Airflow/Astronomer.

Proven experience handling large-scale structured and unstructured datasets, building scalable cloud-based data solutions, and supporting analytics, reporting, and data-driven business initiatives

Key Skills

Education

Any Graduate