{"id":4166923,"url":"https://alion.io/job/sago-data-engineer","title":"Data Engineer","company":{"id":6278,"name":"Sago","domain":"sago.com","url":"https://alion.io/company/sago","size_band":"51-200","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workable","truth_index":{"grade":"A","score":85,"open_postings":5,"ghost_share":0,"stale_share":0.6,"repost_share":0,"time_to_fill_p50_days":41,"computed_at":"2026-11-12T10:38:37Z"}},"role":"Data Science","role_family":"Data Science","seniority":null,"employment_type":"full_time","work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"board_field","remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Gurgaon, India"],"countries":["IN"],"hiring_countries":["IN"],"hiring_countries_total":1,"salary":null,"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Airflow","optional":false},{"name":"Dimensional Modeling","optional":false},{"name":"ETL/ELT","optional":false},{"name":"Git","optional":false},{"name":"Power BI","optional":false},{"name":"pySpark","optional":false},{"name":"Python","optional":false},{"name":"SharePoint","optional":false},{"name":"SQL","optional":false},{"name":"Superset","optional":false},{"name":"Amazon S3","optional":true},{"name":"AWS","optional":true},{"name":"Delta Lake","optional":true},{"name":"Rest API","optional":true},{"name":"Spark","optional":true},{"name":"Trino","optional":true}],"status":"live","first_seen_at":"2026-11-12T13:41:35Z","employer_posted_date":"2026-11-12","last_verified_at":"2026-11-13T03:00:52Z","board_verified":true,"closed_at":null,"days_open":0,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":0},"description":"We are looking for a Data Engineer with 2-5 years of experience to design, build, and maintain reliable data pipelines and analytics-ready datasets. The ideal candidate will have strong SQL and Python or PySpark skills, hands-on experience with cloud data platforms, and the ability to troubleshoot data-quality, performance, and production issues independently.\nKey Responsibilities\n· Design, develop, and maintain scalable ETL and ELT pipelines for batch and scheduled data processing.\n· Build and optimize data transformations using SQL, Python, and PySpark.\n· Ingest and integrate data from databases, APIs, files, SharePoint, and cloud storage.\n· Create and maintain curated, analytics-ready datasets for Power BI, Superset, and other reporting platforms.\n· Implement data-quality checks, reconciliation controls, monitoring, logging, and failure alerts.\n· Troubleshoot pipeline failures, schema mismatches, performance bottlenecks, and data discrepancies.\n· Optimize large-scale data processing for runtime, memory, storage, and cost efficiency.\n· Automate recurring workflows and schedule production jobs using orchestration tools such as Apache Airflow.\n· Maintain technical documentation, data mappings, business rules, and operational runbooks.\n· Collaborate with BI analysts, application teams, and business stakeholders to deliver dependable data solutions.\nRequirements\nRequired Skills and Experience\n· 2-5 years of professional experience in data engineering, ETL development, or a similar role.\n· Strong SQL skills, including joins, common table expressions, window functions, data validation, and query optimization.\n· Hands-on experience with Python and/or PySpark for data processing and automation.\n· Practical experience building and supporting ETL or ELT pipelines in production.\n· Experience working with large datasets, incremental loads, upserts, schema changes, and partitioned data.\n· Good understanding of relational databases, dimensional modeling, data warehousing, and file formats such as Parquet, CSV, and JSON.\n· Experience with Git or another version-control system and structured deployment 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