Data Engineer

Role Overview 1 We are seeking a Data Engineer with strong Python and PySpark expertise to design, build, and support scalable data-processing solutions. The role requires solid engineering discipline, data-quality awareness, and experience working with distributed data workloads.

Key Responsibilities • Design and develop batch and, where required, streaming data pipelines using Python and PySpark. • Transform, validate, and prepare data for analytics, reporting, and downstream consumption. • Optimize Spark jobs for performance, reliability, and efficient resource usage. • Implement monitoring, logging, data-quality checks, and operational support procedures. • Collaborate with data architects, analysts, platform teams, and business stakeholders. • Write tests, maintain technical documentation, and contribute to CI/CD and release processes.

Required Skills and Experience • Strong hands-on Python and PySpark experience. • Good understanding of Spark execution, distributed processing, data partitioning, and performance optimization. • Strong SQL and data-modelling fundamentals. • Experience working with data lakes, warehouses, or large-scale data platforms. • Working knowledge of Linux, Git, automated testing, and deployment practices. • Strong analytical, debugging, and communication skills.

Preferred Skills • Experience with Azure Databricks, Kafka, orchestration tools, and cloud-native data services. • Exposure to data governance, lineage, security, and regulated environments.

Expected Outcomes • Deliver dependable, scalable data pipelines and high-quality datasets. • Improve pipeline performance, observability, maintainability, and operational readiness.

Candidate Profile The ideal candidate is collaborative, accountable, quality-focused, comfortable working in a globally distributed environment, and able to communicate clearly with both technical and business stakeholders.

Exp-6+ Years

NP- Immediate to 15days

Location-Pune (Kharadi)

Interested please share resumes to

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