- Pyspark Data Engineer:
- Hands-on expertise in designing, building, and maintaining Apache Spark pipelines in production environments.
- Proven experience building and scaling data ingestion frameworks that integrate data from multiple source systems, with a focus on reliability, reusability, and scalability.
- Deep understanding of Spark architecture (driver/executors, DAG, partitioning, shuffles, caching, cluster resource management) and experience operating pipelines at scale, including data transformations on datasets 500 GB+.
- Strong understanding of Oracle SQL and HDFS, including handling file formats and applying appropriate data cleansing, normalization, and formatting to produce curated output datasets.
- Ability to write Python, Pyspark, and shell scripts to process, transform, and automate data workflows. The Candidate should be good in writing application programs and automation manual data processing steps using python.
- PySpark Developer / Senior Data Engineer
Skills
- Strong hands-on experience in PySpark, Python, and SQL.
- Experience designing and optimizing Spark-based ETL/ELT pipelines and data processing jobs.
- Strong understanding toa BigQuery.
- Strong understanding of data quality, governance, observability, and performance tuning.
- Good collaboration, debugging, and Agile delivery skills.
Experience
Bachelor's or Master's degree plus 6+ years of data engineering experience with strong PySpark expertise.
