PySpark Developer
Posted Updated
Description
Job Description :
Key Responsibilities :
- Design and develop scalable data processing pipelines using PySpark.
- Develop and optimize ETL/ELT workflows for large and complex datasets.
- Write efficient PySpark and Python code for data extraction, transformation, and loading.
- Perform data cleansing, transformation, aggregation, and validation using PySpark.
- Develop complex SQL queries and optimize data processing workloads.
- Work with structured and unstructured data from databases, APIs, files, and streaming sources.
- Optimize Spark jobs for performance, scalability, memory utilization, and cost efficiency.
- Implement data quality checks, validation, monitoring, and error-handling mechanisms.
- Troubleshoot and resolve data pipeline and production issues.
- Collaborate with Data Engineers, Data Architects, Data Scientists, Analysts, and business stakeholders.
- Participate in code reviews, testing, deployment, and CI/CD activities.
- Ensure data pipelines follow security, governance, and compliance standards.
- Contribute to the design and implementation of reliable, maintainable, and production-ready data solutions.
Required Skills :
- 5 - 10 years of experience in Data Engineering / Big Data development.
- Strong hands-on experience with PySpark and Apache Spark.
- Strong proficiency in Python.
- Strong knowledge of SQL and query optimization.
- Experience with ETL/ELT pipeline development.
- Good understanding of distributed computing and data processing concepts.
- Experience working with large-scale datasets.
- Knowledge of data warehousing, data lakes, and data modelling.
- Experience with cloud platforms such as AWS, Azure, or GCP is preferred.
- Strong debugging, troubleshooting, and performance-tuning skills.
Preferred Skills :
- Experience with Spark SQL, DataFrames, RDDs, and Spark optimization.
- Knowledge of Kafka or other streaming technologies.
- Experience with data platforms such as Databricks, Snowflake, or Hadoop.
- Exposure to Airflow or other workflow orchestration tools.
- Experience with Git, CI/CD, and DevOps practices.
- Understanding of data security, governance, and data quality frameworks.
Preferred Candidate Profile :
- Strong analytical and problem-solving abilities.
- Experience building production-grade and scalable data pipelines.
- Ability to work independently and collaborate effectively with cross-functional teams.
- Strong communication and stakeholder-management skills.
- Good understanding of modern data engineering practices and cloud technologies.