Data Engineer

Description

Position Summary Responsible for the overall management of Medical Affairs Integrated Platform (Pathfinder) systems datamart on Synapse big data platform. The datamart currently consists of about ten different Medical Affairs functional systems/data sources. This resource will maintain and update the data models as needed for robust analytics using Tableau to derive key customer insights. This resource will champion the usage of data in business, and communicate the benefits and return on investment for application and product owners. Understand the data landscape, business needs, and propose/implement innovative solutions. Supports data provisioning and advanced analytics to address clinical or business questions. The ideal candidate will be a seasoned analyst with multiple years of experience leading and managing largescale data analysis projects. The candidate should have demonstrated the ability to actively listen, integrate input from diverse sources and successfully translate medical or business questions into data and analytics requirements, and deliver suitable solutions.
Core Responsibilities Works across global MA teams to gather analytics related business needs/requirements and to apply this information to define the scope and strategic objectives for developing, updating and/or maintaining datamart on Synapse big data platform. Partners with MA business units to ensure requirements are met for reporting and analytics, including development and maintenance of reports/dashboards that assist in identifying signals and trends in Medical Affairs data to promote informed decision making. Work with stakeholders to understand and document data assets, data flows, and reporting/analytical needs. Identify areas where data can be used to improve business activities by defining business users requirements for additional data, metrics, reports, and KPIs. Understand data flows, data collection process, and data repositories. Create and maintain data maps and systems interrelationship diagrams for data domains and systems. Work closely with the data engineers to create optimal physical data models of datasets. Create and maintain metadata and data quality measures and monitoring. Map and blend multiple datasets together into a coherent domain model that represents the business. Define and govern data modeling and design standards, tools, best practices, and related development methodologies for the organization. Set or follow standards for document naming, security, and lifecycle & retention architecture. Make recommendations for standardization and proper data usage of domain models. Assess training needs, creates training material, and delivers technical training on reports/dashboards developed for global MA teams. Partners with the business to deliver coordinated process and technical training. Serves as a Subject Matter Expert (SME) within Medical Affairs for existing systems datamart and potential new additions to the data lake/datamart on Synapse big data platform.
Skills/Knowledge Required Must be a team player and be willing to work in an environment where individual initiative and accountability to the team are required. Strong analytical, problemsolving skills with highly customeroriented application support required. Agile business intelligence and modern data modeling approach. Expertise in data modeling principles/methods including conceptual, logical & physical Data Models. Ability to clearly communicate complex technical ideas, regardless of the technical capacity of the audience. Strong interpersonal skills and ability to work as part of a team. Knowledge of the mathematical foundations is a plus. For example, statistical inference and forecasting such as time series analysis, multivariate analysis, cluster analysis, and optimization. Ability to quickly learn and adapt modeling methods from case studies or other proven approaches. Ability to explore datasets using visualization and querying tools (e.g. SQL). Ability to utilize Business Intelligence tools (e.g. Tableau, Excel, etc) to represent insights. Experience working with dimensionally modeled data. Experience with Big Data technology stack (e.g. Hadoop) on cloud environments (e.g. AWS). Strong written and verbal communication skills and works well across teams. Familiar with IT processes for system implementation and maintenance. Practical knowledge of data governance, quality and stewardship processes