Data Engineer (W2)

Title: Data Engineer

Location: St. Louis, MO

Arrangements: Hybrid engagement (at least 3 days on-site, which include Tuesday and Wednesday)

Interview process: 2 rounds. The first will be via Teams and the 2^nd will be onsite - Will be panel with up to 3 interviewers.

Description:

• Generates reports and regular datasets or report information for end-users, using system tools and database or data warehouse queries and scripts. May create specifications for reports based on business requests.
• Designs, develops and programs methods, processes, and systems to consolidate and analyze structured and unstructured, diverse sources to generate actionable insights and solutions for client services and product enhancement. Analyzes and models data to understand complex business issues and provide insight to decision makers. Integrates data from multiple sources to produce requested or required data elements. Programs and maintains reports, information dashboards, data generators, canned reports and other end-user information portals or resources.
• Uses advanced mathematical and statistical concepts and theories to analyze and collect data; identifies and interprets trends and patterns in datasets.
• Supports complex business problems and issues using unstructured data from internal and external sources to provide insight to decision-makers.
• Builds or defines machine learning / Artificial Intelligence (AI) solutions that create value for the business.

Key responsibilities include:

• Addresses business problems by applying advanced analytics techniques through broad parameters on big, unstructured data sets.
• Designs databases for unstructured data sets, defining how the data will be stored, consumed, integrated and managed.
• Develops optimal techniques and problem-solves to understand and explore multiple reasons for correlations between disparate data sets; provides coaching on how to transform and clean data into an appropriate form for statistical analysis.
• Conducts exploratory data analysis from complex data sources and builds key data sets.
• Works closely with data analysts and data engineers to review and provide feedback on data pipelines and optimization opportunities.
• Translates complex business requirements and technical designs into data science / artificial intelligence solutions aligned to business goals that deliver measurable value to the organization.