{"id":3101747,"url":"https://alion.io/job/rp-sanjiv-goenka-group-data-engineer","title":"Data Engineer","company":{"id":46720,"name":"RP Sanjiv Goenka Group","domain":"rpsg.in","url":"https://alion.io/company/rp-sanjiv-goenka-group","size_band":"5000+","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":"senior","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Delhi, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":20000,"max_usd":44000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":75},"experience_years_min":6,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Airflow","optional":false},{"name":"Amazon Redshift","optional":false},{"name":"Amazon S3","optional":false},{"name":"Apache Kafka","optional":false},{"name":"AWS Glue","optional":false},{"name":"Azure","optional":false},{"name":"Azure Data Factory","optional":false},{"name":"CI/CD","optional":false},{"name":"Databricks","optional":false},{"name":"dbt","optional":false},{"name":"Delta Lake","optional":false},{"name":"ETL/ELT","optional":false},{"name":"Git","optional":false},{"name":"Google BigQuery","optional":false},{"name":"pySpark","optional":false},{"name":"Python","optional":false},{"name":"Snowflake","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false}],"status":"live","first_seen_at":"2026-10-22T17:35:00Z","employer_posted_date":null,"last_verified_at":"2026-10-22T17:35:00Z","board_verified":false,"closed_at":null,"days_open":4,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":4},"description":"We are looking for an experienced Data Engineer with 6-8 years of hands-on experience in designing, building, and managing scalable data pipelines, data platforms, and analytics-ready data assets. The ideal candidate should have strong expertise in data engineering, cloud platforms, ETL/ELT pipelines, data lakehouse architecture, data quality, and production-grade data solutions.\n\nResponsibilities: \nDesign, develop, and maintain scalable data pipelines for structured, semi-structured, and unstructured data.\nBuild and manage data ingestion frameworks from ERP, CRM, SCADA, IoT, Historian, APIs, databases, and external data sources.\nDevelop ETL/ELT workflows for data transformation, cleansing, validation, and enrichment.\nImplement data lake, data warehouse, and lakehouse architectures to support analytics, AI/ML, and reporting use cases.\nEnsure data quality, reliability, lineage, metadata management, and governance across data platforms.\nCollaborate with Data Scientists, ML Engineers, Product Managers, Business Teams, and BI Developers to deliver data solutions.\nOptimise data pipelines for performance, scalability, cost, and reliability.\nBuild reusable data assets, data marts, and curated datasets for business intelligence and AI use cases.\nSupport deployment, monitoring, troubleshooting, and improvement of production data pipelines.\n\nRequirements: \nStrong hands-on experience in SQL, Python, PySpark, and data pipeline development.\nExperience with cloud data platforms such as Azure Data Factory, Azure Synapse, Databricks, ADLS, AWS Glue, Redshift, S3 BigQuery, Cloud Functions, Data Flow, or Snowflake.\nGood understanding of data lake, data warehouse, lakehouse, data modelling, and medallion architecture.\nExperience in batch and real-time/streaming data processing.\nKnowledge of Apache Spark, Kafka, Airflow, dbt, Delta Lake, or similar technologies.\nExperience with data quality, validation, metadata, lineage, and governance frameworks.\nExposure to CI/CD, Git, DevOps practices, and production deployment of data pipelines.\nUnderstanding of APIs, file formats, databases, and enterprise integration patterns.\nSkills\nPySpark, Python, SQL, 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