Python, Pyspark Developer

Build and scale data-driven solutions that power smarter decisions. In this role, you’ll design and deliver high-performance data processing pipelines using Python and PySpark, working closely with data engineers, analysts, and product teams to turn raw data into reliable, actionable insights. You’ll contribute to a collaborative environment where clean code, thoughtful design, and continuous improvement are valued. If you enjoy solving complex data challenges, optimizing distributed workloads, and delivering production-ready systems that make a real impact, this is a great opportunity to grow your expertise while helping teams move faster with trustworthy data. Technical Requirements: Technology->Analytics - Packages->Python - Big Data,Technology->Big Data - Data Processing->PySpark Responsibilities: • Design, develop, and maintain scalable batch/stream data pipelines using Python and PySpark in distributed environments. • Implement efficient transformations, aggregations, and joins on large datasets while ensuring performance and cost optimization. • Write optimized SQL for data extraction, validation, and reconciliation across multiple sources. • Build reusable, testable modules and follow engineering best practices (code reviews, unit testing, documentation). • Troubleshoot production issues, perform root-cause analysis, and implement long-term fixes and monitoring improvements. • Collaborate with stakeholders to translate requirements into technical designs, delivery plans, and measurable outcomes. • Ensure data quality through validation checks, anomaly detection patterns, and consistent schema management. • Contribute to continuous improvement of development standards, performance benchmarks, and pipeline reliability. Preferred Skills: Technology->Big Data - Data Processing->PySpark