Senior Data Engineer - Project Accounting & Finance; St. Louis

PLEASE NOTE: This position requires permanent U.S. work authorization. Candidates requiring current or future visa sponsorship, including those on F-1/OPT, CPT or H1B, are not eligible for this role. This role is not open for staffing partners or corp‑to‑corp candidates.

The Internal WWT IT team is the backbone of our company’s technological infrastructure, ensuring seamless operations and continuous innovation. This team manages and supports our hardware, software, networks, and data systems, while providing top‑notch technical support to employees.

• As a Senior Data Engineer, you will collaborate with a multidisciplinary team of solution architects and data scientists on a wide range of business problems. You will be an integral part of the IT Analytics Delivery group, responsible for building capabilities across business strategy, analytics, and cloud.
• The role’s primary focus will be on architecting and maintaining our data pipeline and ETL processes, building integrations, and developing complex data models to foster data‑driven decision making across all functional areas.

• Independently execute all phases of the Data Engineer project lifecycle.
• Gain subject matter expertise in various business domains.
• Apply technical expertise to solve complex business problems.
• Effectively communicate with business stakeholders for successful project execution.
• Mentor team members.

• Support our Analytics partners embedded in the business, providing data to analysts across the company.
• Be an equal member of a cohesive and self‑less team.
• Take complete ownership of your work with the goal of exceeding customer expectations.
• Work closely with analysts, developers, and data architects to ensure development meets requirements and delivers optimal performance.
• Consult on the design, development, and implementation of innovative solutions to complicated data issues which enhance traditional star‑schema data structures.
• Expertise in Data Engineering and implement multiple end‑to‑end DW projects in a Big Data environment.
• Support and debug issues in the production environment and be part of production support, across several reporting toolsets.
• Work in an agile team—plan, prioritize design, test, and coordinate end‑to‑end delivery of solutions.
• Embrace the opportunity to expand your skillset both functionally and technically.
• Design, create, and implement complex data models (including canonical, conceptual, logical, and physical models).
• Implement new design methodologies.
• Build, scale, and maintain our data infrastructure and data products.
• Implement physical database models and tune SQL.
• Use ANSI SQL and/or PL/SQL to perform data analysis.
• Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and “big data” technologies.
• Flexibility to work as a member of a matrix based diverse and geographically distributed project teams.

• Bachelor’s degree in Computer Science or a minimum of 5 years’ progressive experience in a related field.
• 5+ years of experience in analytics, SQL, and/or ETL development.
• Proficiency in data warehousing/business intelligence development/data modeling.
• 5+ years’ experience building large‑scale data sources in Oracle or an equivalent relational database.
• 3+ years’ experience using API platforms such as Mule Soft / APIGee and ELT platform such as Matillion or Informatica.
• Excellent SQL skills with PL/SQL development experience.
• Hands‑on development experience using an ETL tool;
  Oracle Data Integrator preferred.
• Hands‑on development experience with Oracle Cloud reporting and data replication;
  Business Intelligence Cloud Connector Console, BI Publisher, and OTBI preferred.
• Strong analytical and problem‑solving capabilities.
• Experience with BI reporting tools like Tableau, Power BI.
• Programming skills:
  Java, Scala, Python.
• Expertise with CI/CD pipeline and integration tools e.g., Jenkins, GIT.
• Understand an analytics platform, its use‑cases, and best practices.
• Experience working with different types of data stores (RDBMS, Flat Files,…