Data Scientist

Vertiv is looking for a Data Engineer to build and manage the data infrastructure that powers our smart manufacturing and IoT initiatives for the switchgear and busway business. This position will lead the design, development, and deployment of scalable data pipelines, sourcing mission-critical data from our global network of manufacturing sites and IoT-enabled products. You will be responsible for creating a unified, reliable data foundation that enables advanced analytics, machine learning, and business intelligence to drive operational excellence and innovation across Vertiv.

RESPONSIBILITIES

Programming & Scripting : Python (Pandas, NumPy, Scikit-learn, PyTorch, TensorFlow), R, SQL

Data Engineering & Big Data : Apache Spark, ETL / ELT pipeline architecture, data warehousing

Databases : Relational (PostgreSQL, MySQL) and NoSQL (MongoDB)

Cloud Platforms : AWS (S3, SageMaker), Google Cloud Platform (GCP - BigQuery, Vertex AI), Azure

Machine Learning : Regression, Classification, Clustering, NLP, Time-Series Forecasting

Statistics : Hypothesis Testing, Experimental Design, Bayesian & Frequentist methods

Architect, build, and maintain robust and scalable ETL / ELT data pipelines to process structured and unstructured data from diverse sources including Manufacturing Execution Systems (MES), ERPs, quality control systems, and IoT sensor streams.

Design and implement a centralized cloud data platform (data warehouse / data lake) to serve as the single source of truth for all manufacturing and operational data.

Evaluate, select, and deploy modern data stack technologies (e.g., cloud data warehouses, orchestration tools like Airflow / Prefect, transformation tools like dbt) to establish a best-in-class data infrastructure.

Develop and enforce data engineering “best practices” for data quality, monitoring, logging, data governance, and CI / CD for data pipelines to ensure reliability and trust in the data.

Collaborate closely with data scientists, BI analysts, and manufacturing stakeholders to understand data requirements and deliver production-grade datasets optimized for analytics and machine learning models.

Design and implement standardized data models and schemas to ensure data consistency across the global organization, enabling meaningful cross-plant analysis.

Automate manual data processes and optimize data pipeline performance to decrease data latency, improve data availability, and maximize the ROI of our data assets.

Skills

Expert-level proficiency in SQL and a programming language such as Python or Scala.

Hands-on experience with a major cloud platform (AWS, Azure, or GCP) and its associated data services (e.g., AWS Glue / Redshift, Azure Data Factory / Synapse, GCP BigQuery).

Experience with modern data orchestration and transformation tools (e.g., Airflow, dbt, Prefect).

Strong understanding of data warehousing concepts, data modeling, and database architecture (both relational and NoSQL).

Experience working with manufacturing data (MES, SCADA), supply chain data, or high-volume IoT streaming data (e.g., using Kafka, Kinesis).

Partner with others and foster teamwork, with a “can do” positive attitude and self-motivation.

Manage multiple priorities while working collaboratively!

Results-driven and detail oriented.

EDUCATION AND CERTIFICATIONS

Bachelor’s degree in engineering – Mechanical Engineering, Electrical Engineering, Industrial Engineering, Automation technology or related

Strong Lean Manufacturing & VSM experience, 5-7 years.

Strong knowledge of advanced manufacturing technologies, such as automation, robotics, and additive manufacturing

Proven track record of driving operational excellence and process improvements

Strong analytical and problem-solving skills

Ability to work effectively in cross-functional teams

Expertise in implementing advanced manufacturing technologies + automation and processes

Ability to think strategically and drive change in a dynamic environment

Strong project management skills

Knowledge of industry best practices and emerging trends in advanced manufacturing

PHYSICAL REQUIREMENTS

No Special Physical Requirements

ENVIRONMENTAL DEMANDS

No Special Requirements

TRAVEL TIME REQUIRED

25%

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