Senior Data Engineer

ZipStaff•St. Louis, MO

3d•Onsite

About The Position

ZipStaff is seeking an experienced Senior Data Engineer for an on-site contract role in St. Louis, Missouri, supporting data analysis, reporting, modeling, and insight generation for a major energy and utility organization. The role focuses on designing processes and systems to consolidate and analyze structured and unstructured data from diverse sources, generating actionable insights for client services and product enhancement. The engineer will build reports, dashboards, and data solutions, apply advanced analytical techniques, and support data science- and AI-aligned outcomes.

Requirements

At least 5 years of experience as a Data Engineer or in a similar role focused on data analysis, reporting, modeling, and pipeline support.
Proven experience generating reports and datasets using database or data warehouse queries and scripts.
Strong skills designing and developing processes and systems to consolidate and analyze structured and unstructured data from diverse sources.
Experience analyzing and modeling data to provide insights to decision makers.
Hands-on experience integrating data from multiple sources and programming or maintaining reports, dashboards, and end-user information resources.
Ability to apply advanced mathematical and statistical concepts to identify trends and patterns.
Experience working with unstructured data and supporting complex business problems.
Familiarity with building or defining machine learning or AI solutions that create business value.
Ability to conduct exploratory data analysis, design databases for unstructured data, and coach on data transformation and cleaning.
Strong collaboration skills when working with data analysts, data engineers, and stakeholders.
Ability to work on-site in St. Louis, Missouri.

Nice To Haves

Experience supporting data and analytics initiatives in a regulated utility or energy environment.
Prior work translating business requirements into data science- or AI-aligned solutions.
Background optimizing data pipelines and providing feedback on engineering practices.
Experience with specific tools for data warehousing, reporting, or advanced analytics.

Responsibilities

Generate reports and regular datasets for end users using system tools, database queries, data warehouse queries, and scripts; create report specifications based on business requests.
Design, develop, and program methods, processes, and systems to consolidate and analyze structured and unstructured data from diverse sources.
Analyze and model data to understand complex business issues and provide insights to decision makers.
Integrate data from multiple sources to produce requested or required data elements.
Program and maintain reports, information dashboards, data generators, canned reports, and other end-user information portals or resources.
Apply advanced mathematical and statistical concepts and theories to analyze and collect data and identify and interpret trends and patterns.
Use unstructured data from internal and external sources to address complex business problems and provide decision-maker insights.
Build or define machine learning and artificial intelligence solutions that create business value.
Apply advanced analytics techniques to big, unstructured data sets to address business problems.
Design databases for unstructured data, defining how data will be stored, consumed, integrated, and managed.
Develop optimal techniques to explore correlations between disparate data sets and coach others on transforming and cleaning data for statistical analysis.
Conduct exploratory data analysis from complex data sources and build key data sets.
Collaborate with data analysts and data engineers to review data pipelines and identify optimization opportunities.
Translate complex business requirements and technical designs into data science and artificial intelligence solutions aligned with business goals and measurable value.