Job Description

About WTW
WTW is a leading global advisory, broking and solutions company that helps clients around the world turn risk into a path for growth. With roots dating to 1828, WTW has 45,000 employees serving more than 140 countries. We design and deliver solutions that manage risk, optimize benefits, cultivate talent, and expand the power of capital to protect and strengthen institutions and individuals. Our unique perspective allows us to see the critical intersections between talent, assets and ideas – the dynamic formula that drives business performance. Together, we unlock potential. Learn more at https://www.wtwco.com/en-us.

About the team
Our Health and Benefits business helps large and mid-size clients control health and welfare plan costs, improve health outcomes and promote employee engagement through broad-based, state-of-the-art interventions. We provide solutions encompassing creative plan design, vendor evaluation and management, pricing and funding strategies, data analytics, valuation support, legal compliance and governance strategies. We also provide specialty consulting services including clinical/health management program design, pharmacy solutions, disability/absence management strategies and claims audit services. Product-based solutions such as our pharmacy purchasing coalition round out our broad-based suite of offerings.

We are seeking an experienced Analytic Engineer as part of our Global H&B Data and Analytics Platform. In this role, you will apply data science principles with the technical and architectural expertise of a data engineer. This role will be focused on building robust and scalable data workflows and products, within the semantic layer, to help business stakeholders and analytic teams make data-driven decisions.

Role

• Collaborate with cross-functional team members and other data professionals to define business goals and set parameters to measure analytic outcomes
• Work with data scientists, actuaries and other analytical colleagues to collect and clean data for analysis
• Design, develop and maintain the data models and other data products within the semantic layer.
• Design, develop and maintain data pipelines that are scalable, reusable and governed
• Create and maintain data storage systems within the semantic layer
• Develop and maintain documentation for all data products
• Ensures that all data assets are ready for analysis and decision-making
• University or college degree in Computer Science, Information Systems, Mathematics, Engineering, Statistics, or related field of study.
• 10+ years of experience in Analytics
• 5+ years of relevant experience in a modern data technology stack (e.g. Azure: Synapse, Fabric, ADF AWS: Redshift, Glue, Athena, etc.)
• Strong understanding in Apache Spark or other big data frameworks (e.g. Hadoop); distributed computing experience a plus
• Advanced SQL skills and experience with relational databases and database design
• Intermediate to Advanced level in Python; working knowledge within PySpark a plus
• Strong proficiency in data pipeline and workflow management tools (e.g. Airflow, ADF)
• Strong analytical skills and experience with data modeling
• Strong project management and organizational skills
• Proven ability to work independently and with a team

Requirements

• 10+ years of experience in Analytics
• 5+ years of relevant experience in a modern data technology stack (e.g. Azure: Synapse, Fabric, ADF AWS: Redshift, Glue, Athena, etc.)
• Strong understanding in Apache Spark or other big data frameworks (e.g. Hadoop); distributed computing experience a plus
• Advanced SQL skills and experience with relational databases and database design
• Intermediate to Advanced level in Python; working knowledge within PySpark a plus
• Strong proficiency in data pipeline and workflow management tools (e.g. Airflow, ADF)
• Strong analytical skills and experience with data modeling
• Strong project management and organizational skills
• Proven ability to work independently and with a team

University or college degree in Computer Science, Information Systems, Mathematics, Engineering, Statistics, or related field of study.

Application process

• Application review
• L1 technical interview

• L2 technical interview

  We’re committed to equal employment opportunity and provide application, interview and workplace adjustments and accommodations to all applicants. If you foresee any barriers, from the application process through to joining WTW, please email candidatehelpdesk@wtwco.com