{"id":2693473,"url":"https://alion.io/job/infosys-pyspark-developer","title":"PySpark Developer","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":188,"ghost_share":0,"stale_share":0,"repost_share":0,"time_to_fill_p50_days":92,"computed_at":"2026-11-10T06:52:35Z"}},"role":"Data Science","role_family":"Data Science","seniority":"senior","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":21000,"max_usd":46000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":75},"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"ETL/ELT","optional":false},{"name":"Hadoop","optional":false},{"name":"Linux","optional":false},{"name":"pySpark","optional":false},{"name":"Python","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false},{"name":"Unix","optional":false}],"status":"live","first_seen_at":"2026-10-12T09:33:05Z","employer_posted_date":"2026-10-16","last_verified_at":"2026-11-10T13:19:36Z","board_verified":true,"closed_at":null,"days_open":29,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":29},"description":"We are seeking a highly skilled PySpark Developer with 5-9 years of experience in developing and optimizing large-scale data processing applications. The ideal candidate should have strong expertise in PySpark, Spark SQL, Python, ETL development, and Big Data technologies.\nResponsibilities\nA day in the life of an Infoscion\nAs part of the Infosys delivery team, your primary role would be to interface with the client for quality assurance, issue resolution and ensuring high customer satisfaction.\nYou will understand requirements, create and review designs, validate the architecture and ensure high levels of service offerings to clients in the technology domain.\nYou will participate in project estimation, provide inputs for solution delivery, conduct technical risk planning, perform code reviews and unit test plan reviews.\nYou will lead and guide your teams towards developing optimized high quality code deliverables, continual knowledge management and adherence to the organizational guidelines and processes.\nYou would be a key contributor to building efficient programs/ systems and if you think you fit right in to help our clients navigate their next in their digital transformation journey, this is the place for you!\nIf you think you fit right in to help our clients navigate their next in their digital transformation journey, this is the place for you!\nTechnical requirements\nKey Responsibilities\nDesign, develop, and maintain scalable data pipelines using PySpark.\nDevelop ETL/ELT processes for data ingestion, transformation, and loading.\nWork with large datasets in distributed computing environments.\nOptimize Spark jobs for performance, scalability, and reliability.\nDevelop data processing solutions using Spark SQL, DataFrames, and RDDs.\nIntegrate data from multiple sources, including databases, APIs, and cloud environments.\nCollaborate with data engineers, architects, and business stakeholders.\nPerform troubleshooting and root cause analysis for production issues.\nEnsure data quality, governance, and security standards are followed.\nAdditional responsibilities\nRequired Skills\n5-9 years of experience in Data Engineering or Big Data Development.\nStrong hands-on experience with PySpark and Python.\nExperience with Apache Spark, Spark SQL, DataFrames, and ETL development.\nGood knowledge of Hadoop Ecosystem (Hive, HDFS, YARN).\nStrong SQL and database skills.\nExperience with Unix/Linux environments.\nKnowledge of data warehousing concepts.\nPreferred skills\nTechnology->Big Data - 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