{"id":1031941,"url":"https://alion.io/job/ge-vernova-data-analyst","title":"Data Analyst","company":{"id":6165,"name":"GE Vernova","domain":"gevernova.com","url":"https://alion.io/company/ge-vernova","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":{"grade":"B","score":83,"open_postings":431,"ghost_share":0.009,"stale_share":0.636,"repost_share":0.051,"time_to_fill_p50_days":27,"computed_at":"2026-11-05T05:54:30Z"}},"role":"Analytics","role_family":"Analytics","seniority":"junior","employment_type":"full_time","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":9500,"max_usd":21000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":13},"experience_years_min":2,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"ETL/ELT","optional":false},{"name":"PLEXOS","optional":false},{"name":"PostgreSQL","optional":false},{"name":"Power BI","optional":false},{"name":"Python","optional":false},{"name":"Tableau","optional":false},{"name":"Time Series","optional":false},{"name":"Azure Data Factory","optional":true},{"name":"Databricks","optional":true},{"name":"Docker","optional":true},{"name":"Kubernetes","optional":true},{"name":"Snowflake","optional":true}],"status":"live","first_seen_at":"2026-09-18T14:39:06Z","employer_posted_date":"2026-09-18","last_verified_at":"2026-11-06T02:51:12Z","board_verified":true,"closed_at":null,"days_open":48,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":48},"description":"Job Description Summary\nThe Data Analyst will develop technical architecture and automation support to regional and global GE Vernova Consulting Services team. This role employs a data-centric solutions approach to transform raw power system datasets into high-fidelity actionable insights, enhancing our tactical and strategic market position through robust analytical pipelines.Job Description\nRoles and Responsibilities\nInfrastructure Management: Design, build, and maintain scalable ELT/ETL (Extract, Transform, Load/Extract Transform, Load) pipelines to ingest and transform high-frequency grid data, ensuring data integrity and lineage.\nData Pipeline Automation: Develop advanced Python scripts for data orchestration, automating the extraction of simulation results from production cost and capacity expansion models (e.g., PlanOS, PLEXOS).\nData Modelling & Warehousing: Manage relational database schemas (PostgreSQL) and implement data-lake architectures to optimize storage and query performance for complex power system time-series data.\nVisualization & Business Intelligence (BI): Design and develop high-performance interactive dashboards using Power BI or Tableau that translates complex technical data into clear, actionable insights for key decision-makers. Should be able to use PowerBI, Co-pilot and AI agents to create reports. \nCollaborate with power systems engineers to bridge the gap between simulation outputs and front-end visualization, ensuring seamless integration of grid reliability and economic metrics.\nInnovation: Actively contribute to GE Vernova’s internal data-driven business initiatives, promoting a culture of high-quality data engineering and technical innovation.\nRequired Qualifications\nBachelor’s degree in Computer Science, Data Engineering, Electrical Engineering, or related quantitative field.\n 2-5 years of relevant experience, with proficiency on Python-based automation, database management (PostgreSQL or similar), and sophisticated data visualization.\nDemonstrated proficiency in building end-to-end ELT workflows and managing large-scale datasets, preferably within the energy or utility sector.\nExpertise in Power BI, including advanced data modelling (schemas), data analysis optimization, and Direct Query/Import strategy management.\nStrong analytical skills with an ability to manage multiple complex data priorities across different regions simultaneously.\nPassion for solving challenging technical problems in a collaborative, cross-functional environment.\nDesired Characteristics\nKnowledge of power market modelling, simulation tools (e.g., PlanOS or similar), and an understanding of electric power system fundamentals is a plus. \nProficiency in Cloud data environments (e.g., Databricks, Azure Data Factory, Snowflake) and containerization (Docker/Kubernetes).\nActive participation in industry professional data or engineering societies.\nMaster’s or PhD degree in Computer Science, Data Engineering, Electrical Engineering, or related quantitative field.\nAdditional Information\nRelocation Assistance Provided: 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