Data Engineering Manager - Pharma

About Us:

TheMathCompany or MathCo® is a global Enterprise AI and Analytics company trusted by leading Fortune 500 and Global 2000 enterprises for data-driven decision-making. Founded in 2016, MathCo builds custom AI and advanced analytics solutions to solve enterprise challenges through its hybrid model. NucliOS, MathCo’s proprietary platform, enables connected intelligence at a lower total cost of ownership (TCO).

At MathCo, we foster an open, transparent, and collaborative culture, making it a great place to work. We provide exciting growth opportunities and value capabilities and attitude over experience, enabling our Mathemagicians to 'Leave a Mark '.

Job Description:

We are seeking an experienced Data Engineering Manager with expertise in Pharmaceutical / Life Sciences industry to lead enterprise data and AI initiatives for global clients. This role requires a balance of data engineering leadership, consulting capabilities, and stakeholder management to deliver scalable, business-driven solutions.

The ideal candidate will work closely with business stakeholders, solution architects, and engineering teams to translate complex supply chain challenges into data and AI solutions. This is a managerial, client-facing role focused on delivery leadership, solutioning, and driving business outcomes rather than hands-on development.

Your responsibilities will include:

• Lead end-to-end delivery of data engineering and AI initiatives within the Pharmaceutical / Life Sciences industry.
• Partner with business stakeholders to understand challenges and translate them into scalable data solutions.
• Drive solution design and provide technical oversight for data platforms, analytics, and AI implementations.
• Collaborate with cross-functional teams to deliver data solutions supporting demand planning, inventory optimization, logistics, procurement, and supply chain analytics.
• Guide engineering teams in implementing modern cloud-based data architectures and best practices.
• Work closely with client stakeholders, providing strategic recommendations and ensuring successful project delivery.
• Ensure solutions adhere to enterprise standards for data quality, governance, security, and scalability.
• Contribute to solutioning, capability building, and continuous improvement initiatives.

Skills Required

• Strong understanding of the Pharmaceutical / Life Sciences industry, with experience supporting supply chain, manufacturing, commercial, clinical, or enterprise data initiatives.
• Proven experience leading enterprise-scale Data Engineering and Data Management programs in a client-facing consulting or delivery environment.
• Strong knowledge of modern data platforms and cloud ecosystems including Azure, AWS, Databricks, Snowflake, and enterprise data lakes.
• Experience driving data modernization, cloud migration, master data management, and data governance initiatives.
• Ability to translate complex business challenges into scalable data, analytics, and AI-driven solutions.
• Demonstrated expertise in managing cross-functional teams comprising data engineers, architects, business analysts, and delivery leads.
• Strong stakeholder management skills with the ability to engage and influence senior business leaders, technology teams, and client executives.
• Experience in solution design, effort estimation, delivery planning, risk management, and program governance.
• Strong understanding of Agile delivery methodologies and experience managing large-scale delivery roadmaps.
• Experience leading global and offshore delivery teams while ensuring quality, timeliness, and stakeholder satisfaction.
• Ability to drive strategic discussions around data architecture, platform selection, scalability, performance, and operational excellence.
• Familiarity with AI/ML, Generative AI, and advanced analytics use cases within Pharma and Life Sciences organizations.
• Strong communication, executive presentation, and storytelling skills with the ability to convey technical concepts to non-technical stakeholders.
• Experience managing client relationships, identifying growth opportunities, and supporting business development initiatives.
• Knowledge of industry compliance and regulatory frameworks such as GxP, FDA, GDPR, and data privacy standards is preferred.
• Strong problem-solving, team leadership, and decision-making capabilities with a focus on delivering measurable business outcomes.

Education / Qualification:

• Master’s degree from a top-tier university with a consistent, outstanding academic record OR Bachelor’s degree with 7+ years of relevant work experience.

Years of Experience:

• 10+ years of experience on Data Engineering.
• Minimum 5+ years of experience supporting Pharmaceutical or Life Sciences organizations.
• Demonstrated experience working with offshore delivery models and global stakeholders.

Location: Chicago, IL (Hybrid, 3 – 4 days a week)