Key Responsibilities

- Design, develop, and maintain scalable data pipelines using Python, Hadoop, and Apache Spark.
- Develop efficient data processing and transformation workflows for large datasets.
- Write, optimize, and maintain complex SQL queries and PL/SQL procedures.
- Perform data extraction, transformation, and loading (ETL) from multiple data sources.
- Work with structured and unstructured data to support analytics and reporting requirements.
- Optimize data pipelines and queries for performance, scalability, and reliability.
- Ensure data quality, consistency, security, and integrity across data platforms.
- Collaborate with cross-functional teams to understand business requirements and deliver data engineering solutions.
- Use Git, automation,



and CI/CD practices to support development and deployment.

Required Skills

- 4.5–10 years of experience in software development or data engineering.
- Strong proficiency in AWS
- Hands-on experience with Hadoop and Apache Spark.
- Valuable knowledge of SQL and PL/SQL, including query optimization and stored procedures.
- Experience in ETL development, data processing, and data pipeline design.
- Understanding of data warehousing concepts and distributed computing.
- Strong problem-solving, debugging, and performance-tuning skills.

Skills:- Data engineering, Python, Spark, Amazon Web Services (AWS) and PySpark

📌 Data Engineer (Gurugram)
🏢 wissen technology
📍 Gurugram