Job Description Summary

We are seeking a dynamic, forward-thinking and results-driven Sr Analytics Engineer, who will work on designing, building and maintaining robust data pipelines and reporting solutions on the Steam Data Lake platform. You will operate in a fast-paced Agile environment, ensuring timely and quality delivery of your solutions. You will collaborate with product owners, business stakeholders to understand requirements and translate them into effective analytical solutions. Additionally, you will contribute to Generative AI (GenAI) use cases for the Steam Power Business as needed.

This role will also be responsible to work with other Value Streams across Steam Power to identify areas where the business can leverage common framework for data analytics to drive efficiency, reduce waste and quickly develop POCs to solve critical problems for our customers.
This role will require you to operate with some autonomy within standard practices; lead workstreams as an individual contributor and provides guidance to junior team members.

Job Description

The Senior Analytics Engineer will be responsible for:

• Design and maintain database architectures, schemas, and data models for Steam Datalake

• Build, optimize, and maintain reliable data pipelines for data ingestion, cleaning, transformation, and feature extraction from structured and unstructured sources.

• Build and maintain integrations with internal and external data sources and APIs.

• Establish appropriate data quality checks and follow data governance policies.

• Build insightful data visualization/dashboards using reporting tools like Tableau / Power BI

• Participate in Hackathon’s (AI/Prompt Engineering) to solve business problems

• Work closely with other adjacency functions such as Datascience & Automation to cater relevant data expectations.

• Collaborate with cross-functional teams like AMS, Cloud & Infra, Source (ERP, Salesforce etc.) to develop innovative solutions.

• Participate in Kaizens to support SP Business with IT solutions

• Conduct exploratory data analysis & Identify data quality issues proactively

• Identify areas of tech debt reduction through & implement solutions to reduce tech debt

QUALIFICATIONS/REQUIREMENTS:

• Bachelor's in data science, computer science, computer engineering with hands-on experience in data engineering, or equivalent knowledge or experience.

• Significant experience working in the Data & Analytics space to understand the requirement of both structured and unstructured databases.

• Database management experience with relational (e.g., PostgreSQL) and data warehousing technologies such as, Snowflake, Redshift, Databricks.

• Familiarity with cloud platforms like AWS and/or Azure

• Extensive hands-on experience with ETL (Extract, Transform, Load) tools like Talend, Informatica and automating data pipeline workflows.

• Hands on with data visualization tools such as Tableau, Power BI, or similar platforms for building reports and dashboards.

• Ability of using data scientific programming tools or languages, such as Python, Scala, Java, SQL etc.

• Familiarity with AI/ML and exposure to Prompt Engineering

• Experience with version control systems e.g., Git

• Able to share ideas and work well in a team environment, proactive approach to tasks displaying initiative.

• Flexible and adaptable; open to change and modification of tasks, working in multi-tasking environment.

DESIRED CHARACTERISTICS:

• Self-starter with the ability to work independently, manage ambiguity, and drive analytics solutions from concept to delivery.

• Passion for solving business problem and for emerging technologies such as AI.

• Strong willingness to learn, problem-solving mindset, and collaborative approach to troubleshooting ​

• Innovates and integrates new processes and/or technology to significantly add value to GE VERNOVA. 

• Strong communication skills and a proactive and open approach to conflict resolution.

• Strong organizational skills, self-motivated, and self-directed.

Additional Information