Role Description We're looking for a Data Engineer with a strong foundation in data pipelines and a meaningful edge in AI-native data infrastructure, specifically RAG pipelines, vector search, embedding workflows, and semantic retrieval systems. You'll work on two interconnected problem sets: - Consolidating eight legacy systems into a unified, reliable data platform: ETL pipelines, a data warehouse, and cross-system client identity resolution. - Transforming three decades of institutional research into an intelligent, searchable, interactable knowledge layer that clients can query in ways that weren't possible two years ago. This is a small, senior team. You'll work directly with the CTO, have real architectural ownership, and build systems that are in production. Qualifications - Strong foundation in data pipelines. - Experience with AI-native data infrastructure. - Familiarity with RAG pipelines, vector search, embedding workflows, and semantic retrieval systems. Requirements - Lead the data engineering work for our research portal migration — extracting, transforming, and loading data from legacy systems into modern cloud infrastructure. - Build and maintain ETL/ELT pipelines across multiple integration points: CRM, research distribution platforms, trading systems, and third-party APIs. - Design and implement our “Golden Record” initiative — cross-system client identity resolution across eight legacy databases with no unified identifiers. - Implement event-driven data flows using AWS EventBridge as the central routing layer, treating each source system as a swappable adapter. - Design and build production-grade RAG (Retrieval-Augmented Generation) pipelines over AGCO's research archive — ingestion, chunking strategy, embedding generation, vector storage, and retrieval. - Implement hybrid search approaches that combine semantic (vector) search with keyword and metadata filtering, appropriate for structured financial research queries. - Build and maintain embedding pipelines that keep the vector store current as new research is published, with full observability and freshness guarantees. - Evaluate and implement emerging retrieval strategies as the space evolves: Re-ranking with cross-encoders; Hypothetical Document Embeddings (HyDE); Query expansion and decomposition; Graph-based retrieval (e.g., GraphRAG) for analyst relationship mapping; Structured metadata retrieval for faceted financial queries; Wire retrieval layers into LLM interfaces for research summarization, analyst Q&A, and recommendation-change tracking across the archive. - Apply DataOps practices across all pipelines: version control, CI/CD, environment parity across dev/staging/production, and infrastructure as code. - Monitor pipeline health, embedding freshness, retrieval quality, and LLM call latency — build alerting that catches problems before users do. - Work within our AWS environment (App Runner, EventBridge, CDK) and contribute to IaC best practices. - Partner with the CTO, product team, and application developers to translate business requirements into sound data and retrieval architecture decisions. - Document data flows, schema designs, chunking strategies, and retrieval logic so systems are maintainable and not a black box. - Contribute to evaluation frameworks for retrieval quality — precision, recall, answer faithfulness — so we know when the system is actually working. Company Description

At Capgemini Engineering, the world leader in engineering services, we bring together a global team of engineers, scientists, and architects to help the world’s most innovative companies unleash their potential. From autonomous cars to life-saving robots, our digital and software technology experts think outside the box as they provide unique R&D and engineering services across all industries. Join us for a career full of opportunities. Where you can make a difference. Where no two days are the same. Job Description Your Role: - Plan, manage, and execute releases across all environments - from development to production. - Identify technical and functional interdependencies between various tracks. - Coordinate with all development pods and stakeholders across programs. - Review application code, documentation, and perform pre/post deployment tasks. - Define release process for new data engineering applications. - Change management communication to all required stakeholders. - Execute release packages, step-by-step deployment guides, and command line instructions on production environment. - Support project timelines, clearly setting expectations, and realigning expectations internally as priorities change. - Develop a sound understanding of client’s needs: data conversion and migration requirements, environment management and build processes, deployment planning and execution, solution designs, systems integrations, technical architectures, and infrastructure architectures. Your Profile: - Execute deployment scripts and step-by-step instructions in test and production environments. - Comfortable with Command Line Interfaces. - Understanding of CI/CD, Git branching, packaging and DevOps pipelines. - Working knowledge of data warehousing and reporting technologies: Azure, Databricks, Unity Catalog, Python, Spark, PySpark, Airflow, MicroStrategy, Tableau. #LI-DC10 #LI-Remote Capgemini is a global business and technology transformation partner, helping organizations to accelerate their dual transition to a digital and sustainable world, while creating tangible impact for enterprises and society. It is a responsible and diverse group of 340,000 team members in more than 50 countries. With its strong over 55-year heritage, Capgemini is trusted by its clients to unlock the value of technology to address the entire breadth of their business needs. It delivers end-to-end services and solutions leveraging strengths from strategy and design to engineering, all fueled by its market leading capabilities in AI, generative AI, cloud and data, combined with its deep industry expertise and partner ecosystem.

Job Description: The Data Architect – Senior role leads the design and delivery of enterprise and clinical data architecture solutions. The position provides technical leadership across cloud and on-premise environments while managing multiple complex initiatives and mentoring team members. Please note that a video interview via Microsoft Teams is required, along with potential onsite interviews and meetings. Candidates must not reside in or plan to reside in the following states: California, Connecticut, Hawaii, Illinois, New York, Rhode Island, Vermont, or Washington.Job Details: - Fully Remote - M-F 8-5 - We are not considering candidates that require Visa Sponsorship Essential Functions - Design, implement, and manage scalable data architectures across enterprise and clinical projects - Lead data integration and cloud data strategy initiatives - Manage multiple complex projects aligned to business and clinical goals - Mentor team members and conduct code reviews - Collaborate with cross-functional and clinical stakeholders Skills - Design, implement, and manage scalable data architectures across enterprise and clinical projects - Lead data integration and cloud data strategy initiatives - Manage multiple complex projects aligned to business and clinical goals - Mentor team members and conduct code reviews - Collaborate with cross-functional and clinical stakeholders Minimum Qualifications - Expert SQL skills with extensive experience in relational databases (Oracle, SQL Server, PostgreSQL) - Strong experience with cloud platforms such as AWS, Azure, or GCP - Advanced proficiency in Python and PySpark - Deep knowledge of ETL/ELT tools and processes (traditional and cloud-native) - Strong communication, leadership, and project management skills - Proven experience mentoring technical team members Preferred Qualifications - Education and experience: - Master’s degree in an analytics-related field (e.g., information systems, data science/analytics, statistics, computer science, mathematics) with 4 years of experience, or - Bachelor’s degree in an analytics-related field with 6 years of experience, or - Eight years of professional experience in an analytics-related role. - Experience with Databricks, Apache Spark, and Delta Lake for batch and real-time processing. - Proficiency in data streaming technologies such as Kafka, AWS Kinesis, or Azure Event Hubs. - Experience integrating data via external APIs and developing APIs to deliver data as a product. - Familiarity with CI/CD pipelines for data engineering workflows. - Knowledge of data governance frameworks and regulatory standards (e.g., GDPR, HIPAA). - Experience working in a healthcare environment. - Familiarity with business intelligence tools such as Tableau, Power BI, or Looker. Qualifications Physical Requirements - Remain sitting or standing for long periods of time to perform work on a computer, telephone, or other equipment. Location: Transformation Center Work City: Murray Work State: Utah Scheduled Weekly Hours: 40 The hourly range for this position is listed below. Actual hourly rate dependent upon experience. $54.12 - $85.20 We care about your well-being – mind, body, and spirit – which is why we provide our caregivers a generous benefits package that covers a wide range of programs to foster a sustainable culture of wellness that encompasses living healthy, happy, secure, connected, and engaged. Learn more about our comprehensive benefits package here. Intermountain Health is an equal opportunity employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, age, sex, sexual orientation, gender identity, national origin, disability or protected veteran status. At Intermountain Health, we use the artificial intelligence ("AI") platform, HiredScore to improve your job application experience. HiredScore helps match your skills and experiences to the best jobs for you. While HiredScore assists in reviewing applications, all final decisions are made by Intermountain personnel to ensure fairness. We protect your privacy and follow strict data protection rules. Your information is safe and used only for recruitment. Thank you for considering a career with us and experiencing our AI-enhanced recruitment process. All positions subject to close without notice.

• Own and evolve Measurabl’s data platform architecture—warehousing, ETL/ELT pipelines, data quality frameworks, and data governance practices • Drive data reliability and observability at scale • Establish and enforce data contracts, lineage, and cataloging standards across the organization • Evaluate and adopt modern data stack technologies (e.g., Snowflake, dbt, Airflow, Spark, Kafka) • Define and execute the ML/AI product roadmap • Lead development of production ML systems • Champion the responsible adoption of LLMs and generative AI across the product • Establish MLOps practices • Build and scale sustainability-specific data models, carbon accounting frameworks, and benchmarking analytics • Drive department engagement and performance through hands-on leadership • Define and execute annual strategic plan/focus and department OKRs