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)