Senior Data Engineer

As a Data Engineer, you will be responsible for designing and building efficient data pipelines using Azure Databricks (PySpark). You will implement business logic for data transformation and enrichment at scale, as well as manage and optimize Delta Lake storage solutions. Additionally, you will develop REST APIs using FastAPI to expose processed data and deploy them on Azure Functions for scalable and serverless data access. Your role will also involve developing and managing Airflow DAGs to orchestrate ETL processes, ingesting and processing data from various internal and external sources on a scheduled basis. You will handle data storage and access using PostgreSQL and MongoDB, writing optimized SQL queries to support downstream applications and analytics. Collaboration is key in this role, as you will work cross-functionally with teams to deliver reliable, high-performance data solutions. It is essential to follow best practices in code quality, version control, and documentation to ensure the success of projects. To excel in this position, you should have at least 5 years of hands-on experience as a Data Engineer and strong expertise in Azure Cloud services. Proficiency in Azure Databricks, PySpark, Delta Lake, Python, and FastAPI for API development is required. Experience with Azure Functions for serverless API deployments, managing ETL pipelines using Apache Airflow, and hands-on experience with PostgreSQL and MongoDB are also essential. Strong SQL skills and experience in handling large datasets will be beneficial for this role.,