Role Overview

We are looking for a Big Data Engineer with robust expertise in Databricks, Azure, Python, and Hive to design, build, and optimize scalable data platforms. The ideal candidate will have hands-on experience in ETL/ELT development, Big Data technologies, and up-to-date data lake architectures.

Key Responsibilities
Design, develop, and maintain robust ETL/ELT pipelines for batch and real-time data processing.
Build and manage large-scale data ingestion frameworks for structured and unstructured data.
Monitor, troubleshoot, and optimize data pipelines for performance, reliability, and scalability.
Implement data quality, governance, security, and compliance standards across data platforms.
Develop and support data warehouses, data marts, and data lakes.
Collaborate with Data Governance, Data Quality, Data Architecture, Data Science, DevOps, BI, and business teams to deliver data solutions.




Contribute to data platform modernization and cloud-based analytics initiatives.

Mandatory Skills
Databricks
Azure Data Platform
Python
Hive
SQL

Required Technical Skills
Robust experience in ETL/ELT pipeline development.
Hands-on experience with Apache Spark, Hadoop, and Hive.
Experience with NoSQL and distributed databases such as HBase and Cosmos DB.
Knowledge of Data Warehouses, Data Marts, and Data Lakes.
Experience implementing Medallion Architecture.
Understanding of Data Quality validation frameworks and best practices.
Strong problem-solving and performance tuning skills.

Preferred Skills
Scala development experience.
Exposure to real-time data processing frameworks.
Experience with Azure cloud-native data services.
Knowledge of CI/CD and DevOps practices in data engineering.

📌 Big Data Hive Hyderabad
🏢 Synechron
📍 Hyderabad