Data Analyst - Sr

North American Lighting•Paris, IL

18d

About The Position

The Senior Data Analyst plays a pivotal role in our ongoing digital transformation by advancing data governance, data quality, and trusted analytics across the enterprise. This role blends hands-on analysis and reporting with platform-oriented responsibilities, partnering with business and technical teams to design scalable data solutions, promote data literacy, and deliver actionable insights.

Requirements

Bachelor’s degree in Information Technology, Data Science, Computer Science, or related field.
5+ years in data analysis, data engineering, or data governance roles, including work translating business requirements into scalable data solutions.
Demonstrated success designing and optimizing data pipelines and ETL/ELT processes and ensuring data quality, integrity, and security across multiple systems.
Experience collaborating with cross-functional teams (e.g., engineers, business analysts, architects) and mentoring junior data professionals.
Strong proficiency in SQL; experience with Power BI and SSRS.
Hands-on experience with cloud data platforms (AWS, Azure, or GCP) and/or Palantir Foundry or comparable platforms.
Experience with data modeling (star/snowflake), metadata management, and data cataloging.
Working knowledge of Python for analysis.
Excellent problem-solving skills, attention to detail, and a customer-centric mindset.
Strong communication skills with the ability to promote data literacy and partner effectively with non-technical stakeholders.

Nice To Haves

Master’s degree.
Relevant certifications (e.g., CDMP; platform certifications in Palantir Foundry or Azure).
Exposure to Spark/Databricks.
Industry experience in operations, logistics, or supply chain (automotive experience is a strong advantage).
Experience with virtualization/fabric data architectures, forecasting tools and AI/machine learning (especially Palantir Foundry or Azure).

Responsibilities

Champion data governance policies, standards, and procedures; maintain data dictionaries, business glossaries, and master data frameworks.
Monitor and improve data quality, completeness, timeliness, and lineage across systems; implement controls for accuracy and reliability.
Apply appropriate access controls and ensure compliance with security and privacy requirements and internal policies.
Design, build, and optimize data pipelines and ETL/ELT processes from multiple source systems into enterprise platforms (e.g., Palantir Foundry, cloud data services, SQL data warehouse).
Collaborate with data engineers and architects to model datasets (e.g., star/snowflake schemas) and ensure performance, scalability, and reusability.
Configure and manage ontology/business objects to reflect core processes and support digital twin or operational analytics use cases.
Develop and maintain reports, dashboards, and self-service analytics; translate business requirements into analytical models and KPIs.
Perform advanced analysis to identify trends, anomalies, and opportunities; create forecasts as needed.
Implement data virtualization or federation techniques (as appropriate) to integrate disparate sources for unified analytics.
Partner with cross-functional stakeholders to capture requirements and deliver fit-for-purpose solutions.
Promote data literacy and self-service adoption; provide training, documentation, and best practices to business users.
Investigate and resolve data-related issues; communicate status and remediation plans to stakeholders in a timely manner.
Monitor pipeline health and dashboard performance; log, prioritize, and dispatch support tickets using IT support center software.
Participate in on-call rotation to troubleshoot and resolve systems issues; perform other duties as assigned.