{"id":2331764,"url":"https://alion.io/job/infosys-python-data-processing-3","title":"Python - Data Processing","company":{"id":223,"name":"Infosys","domain":"infosys.com","url":"https://alion.io/company/infosys","size_band":"5000+","is_staffing_agency":false,"employer_type":"services","is_intermediary":false,"listed_via":null,"ats_vendor":"Career site","truth_index":{"grade":"A","score":95,"open_postings":240,"ghost_share":0,"stale_share":0,"repost_share":0,"time_to_fill_p50_days":93,"computed_at":"2026-10-22T06:10:10Z"}},"role":"Backend","role_family":"Backend","seniority":"junior","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Bengaluru, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":8000,"max_usd":22000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":36},"experience_years_min":2,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Anomaly Detection","optional":false},{"name":"ETL/ELT","optional":false},{"name":"pySpark","optional":false},{"name":"Python","optional":false},{"name":"SQL","optional":false},{"name":"Airflow","optional":true},{"name":"Linux","optional":true},{"name":"NumPy","optional":true},{"name":"Pandas","optional":true},{"name":"Spark","optional":true}],"status":"live","first_seen_at":"2026-09-19T08:46:02Z","employer_posted_date":"2026-10-12","last_verified_at":"2026-10-22T12:36:18Z","board_verified":true,"closed_at":null,"days_open":33,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":33},"description":"About the job:\nStep into a role where your Python expertise directly powers reliable, high-quality data movement across systems. As part of a collaborative engineering team, you’ll help design and build scalable data processing solutions that enable faster insights and smoother operations. You’ll work closely with stakeholders to understand data needs, translate them into robust pipelines, and continuously improve performance and stability. This is a great opportunity for someone who enjoys solving real-world data challenges, values clean and maintainable code, and takes pride in delivering dependable systems. If you’re motivated by ownership, teamwork, and building data workflows that others can trust, you’ll feel right at home here.\nResponsibilities\nKey Responsibilities:\nBuild and maintain Python-based data processing components for structured and semi-structured datasets.\nDevelop and support ETL workflows to ingest, transform, validate, and load data into target systems.\nDesign and optimize SQL queries for data extraction, transformation, reconciliation, and reporting needs.\nImplement reliable data pipelines with proper logging, error handling, retries, and monitoring hooks.\nPerform data quality checks, anomaly detection rules, and reconciliation to ensure accuracy and completeness.\nTroubleshoot pipeline failures and performance bottlenecks; drive root-cause analysis and permanent fixes.\nCollaborate with cross-functional teams to gather requirements and deliver incremental improvements.\nMaintain clear technical documentation for pipeline design, data mappings, and operational runbooks.\nTechnical requirements\nPrimary skills: Python - Data Processing/Technology->Big Data - Data Processing->PySpark,Technology->OpenSystem->Python - OpenSystem->Python\nAdditional responsibilities\nMinimum Qualifications:\nBachelor’s degree (or equivalent) in Engineering/Computer Science/IT or related field (BTech/BE/BSc or equivalent).\n2-3 years of hands-on experience in Python for data processing and automation.\nPractical experience building ETL processes and working with data pipelines end-to-end.\nStrong SQL skills including joins, aggregations, subqueries, and performance-aware query writing.\nAbility to write clean, maintainable code and follow basic engineering practices (version control, reviews, testing mindset).\nPreferred Qualifications:\nExperience designing scalable pipeline patterns (incremental loads, CDC concepts, partitioning, backfills).\nFamiliarity with Python data libraries and processing approaches (e.g., Pandas, batch processing patterns).\nExposure to orchestration/scheduling concepts and operationalizing pipelines for reliability and observability.\nExperience working with large datasets and optimizing end-to-end pipeline performance (I/O, SQL tuning, compute efficiency).\nProven ability to collaborate with stakeholders, translate requirements into technical solutions, and deliver within timelines.\nGood to have skills:\nPandas, NumPy, Apache Airflow, Spark (PySpark), Linux/Shell Scripting\nPreferred skills\nTechnology->Programming Languages - 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