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 modern 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

- Strong 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