{"id":2771323,"url":"https://alion.io/job/zingmind-technologies-data-engineer-pythonsqletl","title":"Data Engineer - Python/SQL/ETL","company":{"id":3800616,"name":"ZingMind Technologies","domain":"zingmind.com","url":"https://alion.io/company/zingmind-technologies","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":null,"truth_index":null},"role":"Data Science","role_family":"Data Science","seniority":"middle","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":14500,"max_usd":39000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":21},"experience_years_min":3,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"Azure","optional":false},{"name":"Databricks","optional":false},{"name":"ETL/ELT","optional":false},{"name":"Flink","optional":false},{"name":"GCP","optional":false},{"name":"Google BigQuery","optional":false},{"name":"Hadoop","optional":false},{"name":"Java","optional":false},{"name":"Python","optional":false},{"name":"Scala","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false}],"status":"live","first_seen_at":"2026-08-19T09:25:31Z","employer_posted_date":null,"last_verified_at":"2026-08-19T09:25:31Z","board_verified":false,"closed_at":null,"days_open":71,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":71},"description":"Role : Data Engineer (3-5 Years)\n\nAbout the role : \n\nThese pipelines are critical for powering product analytics, AI model evaluation, safety and reliability systems, and business decision-making across our agentic AI platform.\n\nThis role offers the opportunity to work closely with Product, Data Science, Infrastructure, Marketing, Finance and AI/Research teams, contributing to how our AI systems are trained, evaluated, and improved. 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