Data Analyst

Gevernova gevernova.com Open

Bengaluru Full-time Mid-level Data Analysis & BI

At a glance

Mid-level Data Analysis & BI role at Gevernova. Bengaluru · full-time.

Pay not stated Data Analyst salary

RoleData Analysis & BI

SeniorityMid-level

LocationBengaluru

EmploymentFull-time

PostedSep 18, 2026

Role brief

dataroles summary, based on the employer's posting.

What you'll do

Build and maintain ELT/ETL pipelines that bring in high-frequency grid data while preserving its accuracy and lineage
Write Python automation to extract simulation outputs from production-cost and capacity-expansion models
Shape PostgreSQL schemas and data-lake storage for large power-system time-series datasets
Create interactive Power BI or Tableau dashboards that turn technical results into decision-ready views
Work with power systems engineers to connect simulation outputs with reliability and economic measures

What you bring

A bachelor’s degree in computer science, data engineering, electrical engineering or another related quantitative field
Two to five years of relevant work, including Python automation, database management and advanced data visualization
Hands-on experience building end-to-end ELT workflows and handling large datasets
Strong Power BI skills, including data modelling, performance optimization and choosing DirectQuery or Import

Who this fits

This mid-level role suits someone who can balance several complex data priorities across regions and collaborate with power systems engineers. The position is based in Bengaluru, India, and relocation assistance is available.

From the employer

Job Description Summary

The 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

Roles and Responsibilities

Infrastructure 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.
Data 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).
Data 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.
Visualization & 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.
Collaborate with power systems engineers to bridge the gap between simulation outputs and front-end visualization, ensuring seamless integration of grid reliability and economic metrics.
Innovation: Actively contribute to GE Vernova’s internal data-driven business initiatives, promoting a culture of high-quality data engineering and technical innovation.

Required Qualifications

Bachelor’s degree in Computer Science, Data Engineering, Electrical Engineering, or related quantitative field.
2-5 years of relevant experience, with proficiency on Python-based automation, database management (PostgreSQL or similar), and sophisticated data visualization.
Demonstrated proficiency in building end-to-end ELT workflows and managing large-scale datasets, preferably within the energy or utility sector.
Expertise in Power BI, including advanced data modelling (schemas), data analysis optimization, and Direct Query/Import strategy management.
Strong analytical skills with an ability to manage multiple complex data priorities across different regions simultaneously.
Passion for solving challenging technical problems in a collaborative, cross-functional environment.

Desired Characteristics

Knowledge of power market modelling, simulation tools (e.g., PlanOS or similar), and an understanding of electric power system fundamentals is a plus.
Proficiency in Cloud data environments (e.g., Databricks, Azure Data Factory, Snowflake) and containerization (Docker/Kubernetes).
Active participation in industry professional data or engineering societies.
Master’s or PhD degree in Computer Science, Data Engineering, Electrical Engineering, or related quantitative field.

Additional Information

Relocation Assistance Provided: Yes

Data Analysis & BI work from LinkedIn, X, Reddit and Upwork, in one list.

Each morning you get everything that fits, strongest first.

Data Analysis & BI

Find me work

By the team behind dataroles.

Find me work