Description:
The Senior Manager of Analytics Engineering provides hands-on technical expertise to develop, deploy, and maintain both core data models and core data layer infrastructure. This role is ideal for someone who thrives on building robust, scalable, and well-documented data models and pipelines, while also enabling self-service analytics across the organization.
We are seeking a highly skilled Analytical Engineer to join our team. This role bridges the gap between data engineering and data analytics, focusing on transforming raw data into structured, business-ready datasets. The ideal candidate will be responsible for designing, developing, and implementing analytical workflows, ensuring that data is clean, well-modeled, and optimized for business intelligence and decision-making. This role requires strong technical expertise in data transformation, modeling, and pipeline optimization. Additionally, a successful candidate is an excellent communicator who can effectively explain complex technical information to a wide variety of stakeholders.
Key Responsibilities And Major Duties
- Collaborate with the business to gather requirements and deliver data-products to enable data-informed decision-making.
- As a member of the team, develop a centralized data-layer to deliver data-products at scale to the business.
- Use ELT framework to transform raw or semi-structured data into a contextualized data model, proposing architectural solutions to drive efficiency.
- Partner with AI and ML teams to deliver the data skeleton for AI-enabled internal tools.
- Work within dbt to deliver documented, tested, and DRY (don't-repeat-yourself) code.
- Follow analytical lifecycle process and quality frameworks to deliver accurate data to internal consumers on-time.
- Focus on innovative solutions to increase speed-to-delivery and accelerate business decision-making.
- Independently gather business requirements, establish measurable outcomes, and create analytical product plan translating complexity for various stakeholders.
Qualifications/Degree/Certification/Licensure
- BA/BS or higher required
- Computer Science, Physics, Math, Data Science, Pharmaceutical Science, or Engineering area of study preferred
- Minimum of 5 years of analytical engineering, data modeling or a similar role
- Proficiency with SQL
- Experience scripting (e.g. Python/R)
- Experience with version control (e.g. Git, SVN) and Agile development
- Proven analytical and problem-solving ability
- Expertise gathering requirements to understand business needs and define technical solutions
- Excellent communications and presentation skills. Ability to explain complex analyses and outcomes to both technical and non-technical stakeholders
- Hands-on experience with dbt a plus
- Familiarity with AI, ML, predictive modeling a plus
- Knowledge of data engineering tools (Airflow) and visualization tools (Tableau, Power BI, Looker)
- Familiarity with our toolkit desired: work information process tools (JIRA, Confluence, ServiceNow, MS suites); data-related tools (Oracle, Redshift, PostgreSQL, CDP Impala, Athena)
- Proven experience in guiding large, complex projects that involve collaborating with team members from various functions.