Lead Data Product Analyst

Job Title : Lead Data Product Analyst

Location: Oak Brook, Illinois (Hybrid – in-office Monday through Wednesday required)

About The Company

Our client is a global technology-driven manufacturer that has evolved into a modern, data-first enterprise. Originally rooted in industrial excellence, the company now applies data, AI, and advanced analytics to reimagine operations, customer experience, and product innovation. Cross-functional teams in data engineering, product, and analytics work closely together to build scalable data solutions that power smarter decisions across the business.

Job Summary

We are seeking a Lead Data Product Analyst with a strong data engineering background to help design, build, and scale the company’s data products and platforms. This role requires a deep understanding of how data moves through systems — from ingestion and transformation to modeling and delivery — as well as the ability to translate business needs into technical requirements that deliver measurable outcomes.

The ideal candidate will be fluent in SQL, Azure, and Python, experienced in developing or guiding data pipelines, and able to partner effectively with engineering and business teams. This individual will own the full lifecycle of data product development and serve as a connector between technical execution and strategic business value.

Key Responsibilities

• Lead the design, development, and delivery of scalable, high-quality data products supporting key enterprise initiatives.
• Apply data engineering principles to ensure data pipelines, models, and architectures are optimized for performance and quality.
• Partner with data engineers and architects to design robust, reusable data assets that support analytics, AI, and digital applications.
• Collaborate with business stakeholders to define data product requirements, ensuring alignment with strategic goals and technical feasibility.
• Define and implement best practices for data governance, lineage, and documentation across products and platforms.
• Translate complex business logic into efficient SQL and Python-based data transformations.
• Mentor nearshore contributors and foster collaboration across data engineering and analytics teams.
• Serve as a bridge between technical and non-technical stakeholders, communicating data concepts clearly and effectively.
  
  

Requirements

• Education:
• Bachelor’s degree in Computer Science, Data Engineering, Information Systems, or a related field.
• Experience:
• 8+ years of experience in data product management, data engineering, or advanced analytics.
• Strong hands-on foundation in data engineering — must understand how to design, build, and maintain pipelines and models.
• Proven experience delivering end-to-end data products in cloud environments.
• Experience working in large, complex enterprise or consulting settings.
• Technical Skills:
• SQL (expert level) — the primary technical tool (majority of daily work).
• Azure cloud experience required; Databricks strongly preferred.
• Python proficiency for data transformation and pipeline validation.
• Deep understanding of data modeling, ETL/ELT processes, and data architecture concepts.
• Familiarity with data visualization and BI platforms (Power BI, Tableau, Qlik).
• Experience with cloud-based environments such as Azure Synapse, ADLS Gen2, or AWS equivalents.
• Other Skills:
• Strong communication and stakeholder management skills.
• Ability to translate between business strategy and technical implementation.
• Consultative approach with the confidence to challenge assumptions and propose scalable solutions.
• Hands-on and proactive — capable of diagnosing, architecting, and improving data flows.
  

Preferred Qualifications

• Experience with Databricks, Azure Synapse, Event Hubs, or Kafka.
• Background as a software developer or data engineer before moving into data product roles.
• Master’s degree or data-related certifications (Azure, AWS, Databricks).
• Prior experience mentoring contractors or leading small teams.
  
  

Compensation & Benefits

• Salary: $145,000 – $165,000 base
• Bonus: 15% annual bonus (based on individual and company performance)
• Comprehensive health, dental, and vision coverage
• Hybrid work structure (in-office Monday through Wednesday required)
• Career development in a collaborative, innovation-driven data organization