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Python - Data Processing

Infosys

3.5
259 reviews
Infosys
Job Type   /   Job Level
Full-time   /   Others/Any
Job Location
Bengaluru East, Karnataka, India
Salary Range
INR 85,000 - INR 140,000 (Monthly)
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  • Primary skills: Python - Data Processing/Technology->Big Data - Data Processing->PySpark,Technology->OpenSystem->Python - OpenSystem->Python

Key Responsibilities:

  • Build and maintain Python-based data processing components for structured and semi-structured datasets.
  • Develop and support ETL workflows to ingest, transform, validate, and load data into target systems.
  • Design and optimize SQL queries for data extraction, transformation, reconciliation, and reporting needs.
  • Implement reliable data pipelines with proper logging, error handling, retries, and monitoring hooks.
  • Perform data quality checks, anomaly detection rules, and reconciliation to ensure accuracy and completeness.
  • Troubleshoot pipeline failures and performance bottlenecks; drive root-cause analysis and permanent fixes.
  • Collaborate with cross-functional teams to gather requirements and deliver incremental improvements.
  • Maintain clear technical documentation for pipeline design, data mappings, and operational runbooks. Minimum Qualifications:
  • Bachelor’s degree (or equivalent) in Engineering/Computer Science/IT or related field (BTech/BE/BSc or equivalent).
  • 2–3 years of hands-on experience in Python for data processing and automation.
  • Practical experience building ETL processes and working with data pipelines end-to-end.
  • Strong SQL skills including joins, aggregations, subqueries, and performance-aware query writing.
  • Ability to write clean, maintainable code and follow basic engineering practices (version control, reviews, testing mindset). Preferred Qualifications:
  • Experience designing scalable pipeline patterns (incremental loads, CDC concepts, partitioning, backfills).
  • Familiarity with Python data libraries and processing approaches (e.g., Pandas, batch processing patterns).
  • Exposure to orchestration/scheduling concepts and operationalizing pipelines for reliability and observability.
  • Experience working with large datasets and optimizing end-to-end pipeline performance (I/O, SQL tuning, compute efficiency).
  • Proven ability to collaborate with stakeholders, translate requirements into technical solutions, and deliver within timelines. Good to have skills: Pandas, NumPy, Apache Airflow, Spark (PySpark), Linux/Shell Scripting
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