Manager, Data Solutions

Havi•Chicago, IL

31d•$115,000 - $125,000•Hybrid

About The Position

Innovate and institutionalize data management solutions to continuously enhance the quality of our analytic products in supply chain visibility, optimization, forecasting, and planning. Lead a group of skilled data analysts and data engineers to design, develop, and implement scalable and performant data management and quality assurance solutions to support our products globally. Collaborate with Product, Process, and Technology teams to ensure alignment with overall strategic and commercial needs. This is a hybrid role based at 345 N Morgan St, Chicago, IL 60607. Candidates must reside in the Chicago metropolitan area. Relocation assistance is not offered at this time.

Requirements

Bachelor's degree in computer science, engineering or closely related field; advanced degree preferred
4+ years of managing, developing, and deploying scalable data management and governance frameworks supporting analytics and operational systems.
Proven experience defining and enforcing enterprise data governance policies, including metadata management, data lineage, master data management (MDM), data cataloging, and access control aligned with corporate and regulatory standards.
Strong working knowledge of data stewardship, data quality monitoring, and data lifecycle management processes across multiple business domains.
Demonstrated expertise in building and optimizing data pipelines and integration workflows leveraging modern cloud technologies (Azure Data Factory, Databricks, Synapse, Spark) within a metadata-driven architecture.
Experience collaborating with Data Engineering teams to translate business rules into robust ETL/ELT logic, ensuring consistent and trusted data ingestion, transformation, and distribution.
Skilled at data modelling (conceptual, logical, and physical) and schema design for analytical and operational workloads across data lakes and warehouses.
Hands-on experience automating data operations, including pipeline orchestration, validation, alerting, and SLA tracking through DevOps tools, CI/CD workflows, and Infrastructure-as-Code practices.
Proficiency in implementing observability frameworks to monitor data pipeline health, latency, and data quality metrics through tools such as Great Expectations, Monte Carlo, or native Azure monitoring.
Experience managing data access, security, and compliance controls aligned with internal governance and external standards (e.g., GDPR, CCPA, SOX).
Proven ability to operationalize data governance by embedding quality, lineage, and stewardship principles into day-to-day engineering and analytics workflows.
Deep understanding of Agile DataOps practices and continuous improvement cycles, integrating feedback from data consumers to enhance the availability, reliability, and reusability of data assets.
Experience with Python, Databricks, AI and GenAI frameworks and tools, Prompt engineering, Azure or equivalent cloud technologies, data model architectures.
Adept at collaborating with cross-functional teams (Technology, Analytics, Data Science, and Business) to align governance policies, data definitions, and KPIs for consistent enterprise reporting.
Strong communication skills with the ability to articulate technical and governance concepts in business language to both internal and client stakeholders.
Experience in driving revenue and profit growth through data analytics

Responsibilities

Responsible for working with the Director of Global Analytics and Insights to define, design, develop, evolve, and implement data processes and solutions globally
Responsible for establishing and maintaining data standards and governance
Responsible for ensuring continuous data availability and assuring data quality
Responsible for building and maintaining a monitoring framework that captures operational KPI for data pipeline health, data quality, and performance
Develop a scalable operations model to include documented release procedures, communication, and roadmap
Collaborate with Technology to understand current architecture and infrastructure and to drive improvements to better serve the business needs
Collaborate with source data application owners to ensure data integrity
Manage service levels, ensuring data solutions are fully supported to their SLAs
Deliver Traceability service to customers and other key stakeholders
Drive thought leadership in areas such as Gen AI/Agentic AI/ML and other recent advancements in data and technology
Participating fully and collaborating with the broader analytics teams in developing customer relevant models and solutions
Drive customer satisfaction and value creation
Train, develop, and mentor other analytics team members
Strengthen cross functional relationships
Ensure alignment with revenue and profit goals for Global Planning and Analytics