Analytics Engineer

• Design, build, and maintain end-to-end data pipelines — from raw source ingestion through transformation, modeling, and delivery — with reliability and performance in mind
• Develop and extend dbt models on top of Acrisure's data warehouse, with particular focus on the operational and SSOT data layers that underpin enterprise reporting
• Build Palantir Foundry applications, Ontology objects, and workflows that surface data to analysts and business stakeholders in forms they can act on moving the team beyond ad hoc querying toward scalable, reusable tooling
• Partner closely with analysts and business intelligence teammates to understand downstream needs and engineer upstream data assets accordingly
• Uphold data modeling best practices in the work you touch: clear documentation, version control via Git, incremental build strategies, and data quality testing
• Leverage AI tools (Claude, Palantir AI FDE, Gemini, and others) to accelerate development, while applying rigorous critical evaluation to any AI-generated code or logic before it ships
• Contribute to the pod's overall data strategy, surface infrastructure gaps, raise architectural improvements, and help shape how the Growth & Placement pod's data layer evolves

Analytics Engineer, Growth & Placement

• Management of design cost reduction activities, focusing on development of global strategic processes and tools, as well as leading the development of global cost applications and dashboards to facilitate collaboration between the global team.
• Responsibilities also include complex data analysis, presentation, communication, and benchmarking to evaluate and compare part designs, features and technologies of internal benchmarks along with other OEMs.
• Additionally, the role involves KPI development, reporting and program management to ensure delivery of the identified cost reduction actions.

Global Total Cost and TVM Data Analytics Engineer

• Consult with teams across the organization to translate key product and business processes into technical data requirements. Use dbt, BigQuery, and SQL to build up Packback’s metrics layer to enable self-serve access to core analytics.
• Build, optimize, and orchestrate data pipelines with dbt, Airflow, and Python
• Establish data integrity standards and SLAs to ensure timely, accurate delivery of data
• Build insightful and reliable dashboards to track performance of core company metrics across the product and business
• Collaborate with business operations teams to define and train on best practices with respect to data modeling, analytics, and visualization
• Collaborate with leadership to conduct analyses and apply statistical methods to answer day-to-day questions or support larger initiatives
• Work within Packback’s research function with partner institutions and perform in-depth analyses to understand how Packback’s products are driving key student outcomes
• Consult on the adoption of new technologies that impact Packback’s data infrastructure

• Provides financial and regulatory reporting and analyses to maintain adequate controls over the financial and regulatory reporting processes
• Responsible for running complex business performance, risk and operational analytics
• Develops analytical methods/models to assess market, credit and/or operational risk of new and existing financial products
• Leverages business/product expertise to rigorously analyze large datasets, improve risk adjusted returns, deliver profitable growth, and communicate conclusions
• Synthesizes analytical results and develops, recommends, and implements business strategies that improve lending decisions, assist in managing risk, increase revenues, reduce exposure to losses, meet business goals, and improve performance
• Establishes baselines for strategies and tracks actual performance to expectations
• Applies predictive models, third party data, and other tools to develop and execute appropriate segmentation and targeting for acquisition and portfolio strategies to provide insight into portfolio risk
• Manages engagements with internal and external information suppliers ensuring solution is fit for purpose while maintaining appropriate governance and oversight
• Works with business, credit, data, and model development partners to design, develop, and monitor test designs and analytical reporting to track and enhance strategies
• Designs/enhances standard reporting suites for regular product/portfolio reviews
• Collaborates with the line of business, Finance, and Risk partners to assess and establish credit risk appetite and to understand its implications, as well as to establish policies and procedures governing the identification, monitoring, and management of risk appetite.

Portfolio Analytics & Strategy Specialist – Data, Modeling & Analytics

• Develop scalable, standardized automation solutions for data centers
• Translate customer requirements into robust system architectures and application concepts
• Partner with Sales, Key Account teams, Global Solution Centers, and ecosystem partners
• Lead the technical definition of integrated automation solutions
• Support the transition from presales to execution by providing technical guidance
• Capture customer and field feedback to enhance standardized solution architectures

Senior Applications & Solutions Engineer, Data Centers – ABB Robotics

• Lead the requirements documentation and coordination by developing Behavior Technical Specifications (BTS’s) for chassis diagnostics and analytics projects and translating these to project initiatives, capabilities, and features.
• Create and maintain requirements for serial data and service-level diagnostics (ex. RIDs/DIDs) using “On-board Diagnostic Principles” and communication services.
• Organize and approve requirements written by other group members.
• Maintain privacy impact assessments for the data that the group collects and uses.
• Manage the data element tracking and sourcing strategy for the chassis space, including establishing required data elements, documenting source databases and tables, and proposing proper collection cadences.
• Develop and manage supplier data-sharing contracts.
• Develop and manage requirements for the data collection initiatives, capabilities, and features throughout the group by working with our IT teams to Demonstrate exceptional communication skills while reporting out to leadership (on a regular cadence) the progress of diagnostics and analytics development.
• Lead failure mode effects analysis and test regime discussions with our diagnostics and analytics developers.

Senior Diagnostics & Analytics Sub-System Lead Engineer – Chassis

• Define, prototype, and productionize safety and performance metrics for automated driving systems.
• Establish analytic approaches and sufficiency criteria that support safety assessment, development decisions, and launch readiness.
• Support proactive safety monitoring and targeted investigations tied to specific system-performance or safety questions.
• Apply engineering and physics-based methods to process raw signals and derive meaningful representations of vehicle motion, driving context, and system behavior.
• Create interactive visualizations and reporting artifacts that communicate safety insights clearly, enhance transparency, and reduce barriers to interrogating source data in support of technical decision-making.

Analytics Engineer, AV Safety Engineering

• Design and develop data serving and semantic layers to support business needs ranging from traditional reporting to reverse ETL and LLM/AI implementations.
• Develop data models for use by analysts and applications from across the business using modern dimensional modeling practices to efficiently serve accurate, consistent data.
• Build and maintain robust, scalable data pipelines to extract, transform, and load (ETL, ELT) data from various sources into the data platform using both batch processing and event-driven patterns.
• Create efficient, performant data models to support business requirements and analytics needs.
• Implement and automate data quality checks and monitoring to ensure data accuracy and drive observability.
• Manage, troubleshoot and optimize existing data infrastructure, including cloud-based solutions and on-premises systems.
• Leverage cloud data platforms (Fabric, Databricks, Snowflake, etc.) for data storage, processing, and analysis.
• Work closely with data analysts, data scientists, and business stakeholders to understand their data needs and deliver solutions.
• Identify and resolve data-related issues and challenges for technical and non-technical stakeholders.
• Support company-wide projects ranging from server migrations to mergers and acquisitions as a data and systems expert.
• Automate data processes to improve efficiency and reduce manual effort.
• Implement modern concepts like metadata-driven pipelines and Infrastructure-as-Code that will play a key role in a scalable, resilient data platform.
• Document data processes, architecture, and workflows.

Analytics Engineer jobs in Missouri

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Analytics Engineer, Growth & Placement

Global Total Cost and TVM Data Analytics Engineer

Analytics Engineer

Portfolio Analytics & Strategy Specialist – Data, Modeling & Analytics

Senior Applications & Solutions Engineer, Data Centers – ABB Robotics

Senior Diagnostics & Analytics Sub-System Lead Engineer – Chassis

Analytics Engineer, AV Safety Engineering

Analytics Engineer