Big Data Engineer
Posted 5
views
Summary
An experienced Big Data Engineer who designs, builds, and tunes scalable data pipelines using PySpark and the Hadoop ecosystem (HDFS, Hive, Sqoop), writes large-scale SQL/HiveQL/PLSQL queries, and orchestrates workflows with Airflow or Oozie in an Agile team. Based in Pune or Nagpur, India, full-time, 6+ years of experience required.
Big Data Engineer
Location: Pune/Nagpur
Experience: 6+ Years
Employment Type: Full-time
Job Overview
We are looking for an experienced Big Data Engineer with strong expertise in PySpark and Big Data ecosystems. The ideal candidate will be responsible for designing, developing, and optimizing scalable data pipelines while ensuring high performance and reliability.
Key Responsibilities
- Design, develop, and maintain data pipelines using PySpark and related Big Data technologies.
- Work with HDFS, Hive, Sqoop, and other tools in the Hadoop ecosystem.
- Write efficient HiveQL, PLSQL and SQL queries to handle large-scale datasets.
- Perform performance tuning and optimization of distributed data systems.
- Collaborate with cross-functional teams in an Agile environment to deliver high-quality solutions.
- Manage and schedule workflows using Apache Airflow or Oozie.
- Troubleshoot and resolve issues in data pipelines to ensure reliability and accuracy.
Required Skills
- Proven experience in Big Data Engineering with a focus on PySpark.
- Strong knowledge of HDFS, Hive, Sqoop, and related tools.
- Proficiency in SQL/PLSQL/HiveQL for large datasets.
- Expertise in performance tuning and optimization of distributed systems.
- Familiarity with Agile methodology and collaborative team practices.
- Experience with workflow orchestration tools (Airflow/Oozie).
- Strong problem-solving, analytical, and communication skills.
Good to Have
- Knowledge of data modeling and data warehousing concepts.
- Exposure to DevOps practices and CI/CD pipelines for data engineering.
- Experience with other Big Data frameworks such as Spark Streaming or Kafka.