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UnitedHealth Group is a healthcare and well-being company that’s dedicated to improving the health outcomes of millions around the world. We are comprised of
Role Description We are seeking a highly skilled Senior Data Engineer to design, build, and optimize scalable data and AI platforms on Azure. This role will focus on enabling enterprise data pipelines, real-time processing, and AI/ML model integration using Databricks and modern cloud technologies. You will enjoy the flexibility to telecommute* from anywhere within the U.S. as you take on some tough challenges. - Design and develop scalable data pipelines using Databricks, Apache Spark, and Python on Azure - Build cloud-native solutions leveraging Azure Data Lake, Azure Data Factory, and Delta Lake - Collaborate with Data Science and AI teams to operationalize ML models and embed them into production workflows - Develop and maintain feature stores, model input pipelines, and real-time/streaming frameworks - Ensure data quality, governance, and security across the full data lifecycle - Build reusable frameworks, accelerators, and automation scripts to improve engineering efficiency - Optimize performance, scalability, and reliability of data workflows and batch/streaming pipelines - Participate in Agile development processes, including sprint planning, code reviews, and CI/CD pipelines - Provide production support and on-call coverage, ensuring system stability and rapid issue resolution - Design, develop, and deploy AI-powered solutions to address complex business challenges with emphasis on responsible use of AI Qualifications - Bachelor’s degree in Computer Science, Engineering, or IT related field - 6+ years of experience in Data Engineering with Python/PySpark - 6+ years of experience in building ETL/ELT pipelines using Databricks - 6+ years of experience working in Agile environments - 5+ years of strong experience in SQL / PL-SQL - 4+ years of experience with Azure Databricks and Delta Lake architecture - 4+ years of hands-on experience with CI/CD (GitHub Actions, Azure DevOps) - 3+ years of hands-on experience with Azure cloud services (ADF, ADLS, Databricks) - 2+ years of experience with Databricks Delta Live Tables (DLT) - 2+ years of experience with unit testing, validation, and pipeline testing frameworks Requirements - Familiarity with medallion architecture and SCD2 implementations - AI builder: Design, develop, and deploy AI-powered solutions to address complex business challenges with emphasis on responsible use of AI - Experience building enterprise-scale data platforms - Strong skills in performance tuning and debugging large-scale pipelines - Experience with real-time/streaming frameworks (Structured Streaming) - Ability to work in distributed, cross-functional global teams - Exposure to GenAI tools (e.g., GitHub Copilot) for engineering productivity - Strong understanding of secure coding practices and vulnerability remediation - Proven ability to analyze logs, troubleshoot production issues, and optimize performance - Demonstrated capability to design and deploy AI-powered solutions responsibly Benefits - Comprehensive benefits package - Incentive and recognition programs - Equity stock purchase - 401k contribution (all benefits are subject to eligibility requirements)
We help clients turn data into decisions no matter where it lives-in apps, on-prem, in a hybrid model, or in the cloud.
Role Description We are seeking a skilled Oracle Fusion Data Intelligence (FDI) Integration Consultant to support the integration and data pipeline aspects of an FDI implementation for a client that has already deployed Oracle Cloud ERP. This role will focus on ensuring seamless, accurate, and efficient data movement from Oracle Fusion ERP into FDI using standard, out-of-the-box integration capabilities, with no customizations or extensions. The consultant will work under the direction of the FDI Functional Lead and in close coordination with the configuration team to ensure data readiness, integrity, and alignment with Oracle-delivered analytics content. Job Responsibilities - Implementation Leadership - Lead end-to-end implementation of Oracle Fusion Data Intelligence (FDI) aligned with an existing Oracle Cloud ERP footprint. - Drive an OOTB-first approach, leveraging standard subject areas, KPIs, and dashboards without customization. - Ensure strict adherence to Oracle recommended configuration practices and implementation playbooks. - Functional Design & Alignment - Partner with business stakeholders (Finance, Procurement, Projects, etc.) to: - Understand reporting and analytics needs. - Map requirements to pre-delivered FDI content. - Facilitate design workshops focused on fit-to-standard rather than bespoke solutions. - Identify gaps and guide stakeholders toward process alignment vs. system customization. - Configuration & Setup - Oversee configuration of: - Prebuilt dashboards and KPIs. - Role-based analytics access. - Data pipelines and refresh schedules. - Validate data integration between Oracle ERP and FDI environments. - Data Validation & Quality - Ensure accuracy and consistency of data flowing from Oracle Fusion ERP into FDI. - Lead data reconciliation and validation efforts across modules. - Establish data governance practices supporting analytics reliability. - Stakeholder Engagement - Communicate implementation progress, risks, and decisions to stakeholders. - Provide executive-level insights on analytics capabilities and business value. - Drive user adoption through clear messaging on OOTB benefits. - Testing & Deployment - Lead functional testing (SIT/UAT) focused on validating standard analytics outputs. - Coordinate business user acceptance of dashboards and reports. - Support go-live readiness and hypercare activities. - Change Management & Adoption - Promote adoption of delivered content with minimal deviation. - Support training efforts focused on how to use standard dashboards effectively. - Advocate for business process alignment to maximize FDI value. Qualifications - Bachelor’s degree in Information Systems, Business, Finance, or related field. - 7+ years in Oracle analytics or ERP reporting roles. - 3+ years with Oracle Fusion Analytics / Fusion Data Intelligence (FDI) or Oracle Analytics Cloud (OAC) in a Fusion environment. - Strong functional knowledge of Oracle Cloud ERP modules (e.g., Financials, Procurement, Projects). Key Skills & Expertise - Functional Expertise - Deep understanding of Oracle Fusion ERP data structures. - Prebuilt FDI subject areas and KPIs. - Experience delivering fit-to-standard implementations. - Analytics & Familiarity - Oracle Fusion Data Intelligence platform. - Oracle Analytics Cloud dashboards and semantic models. - Ability to interpret and explain analytics to business users. - Implementation Approach - Proven ability to enforce no-customization / OOTB-first strategies. - Drive stakeholder alignment around standard capabilities. - Soft Skills - Strong facilitation and stakeholder management skills. - Excellent communication (executive-level storytelling). - Ability to influence business decisions toward best practices. Preferred Qualifications - Prior experience leading FDI implementations post-ERP go-live. - Experience in data governance and data quality frameworks. - Knowledge of Oracle’s quarterly update cadence and impact on analytics. - Certifications in Oracle Cloud ERP or Analytics (preferred).
Role Description We're looking for a Data Engineer to join our team, building and maintaining the data infrastructure that powers a cloud-based case management system for a major federal financial regulatory agency. - Build and maintain data marts, materialized views, and data pipelines within an AWS Aurora PostgreSQL environment. - Support data integration between the core system and downstream platforms including MicroStrategy and enterprise reporting tools. - Design and optimize data workflows that support analytics, reporting, and operational decision-making. - Monitor data pipeline health and troubleshoot performance and data quality issues. - Collaborate with engineering and product teams to support new data-driven features. - Support compliance with federal data security requirements including FISMA and NIST 800-53. Qualifications - Strong proficiency in SQL and experience working with PostgreSQL or similar relational databases. - Experience building and maintaining data marts, materialized views, or ETL/ELT pipelines. - Familiarity with AWS data services and cloud-based data infrastructure. - Experience integrating with enterprise reporting or BI tools such as MicroStrategy is a plus. - Understanding of data security and governance in federal or regulated environments is a plus. - Thrives in a remote, collaborative Agile environment and genuinely enjoys working closely with a cross-functional team. - Communicates clearly and openly, whether documenting data flows or collaborating with engineers on integration design. - Performs other related duties as assigned. Requirements - Applicants must be authorized to work in the United States. - In alignment with federal contract requirements, certain roles may also require U.S. citizenship and the ability to obtain and maintain a federal background investigation and/or a security clearance. - Education: Bachelor's Degree. Benefits - Fully remote. - Tech & Education Stipend. - Comprehensive Benefits Package. - Company Match 401(k) plan. - Flexible PTO, Paid Holidays. Company Description Oddball is an Equal Opportunity Employer and does not discriminate against applicants based on race, religion, color, disability, medical condition, legally protected genetic information, national origin, gender, sexual orientation, marital status, gender identity or expression, sex (including pregnancy, childbirth or related medical conditions), age, veteran status or other legally protected characteristics. Any applicant with a mental or physical disability who requires an accommodation during the application process should contact an Oddball HR representative to request such an accommodation by emailing hello@Oddball.io. At Oddball, it’s important each employee is compensated competitively and fairly. In alignment with state legal requirements, a range for the included position is listed below. Be advised, actual offer details are determined by job category, job location, and candidate skill level. United States Wage Range: $100,000 - $140,000.
A certified Great Place to Work®, the American College of Radiology is the voice of #radiology.
Role Description The ACR seeks a Team Lead to provide Data Management leadership to the ACR study initiatives across the College. - Provides vision, leadership, and mentoring to a team of Data Management professionals; - Oversees and leads review of protocols and coordinates study start-up and active study management activities for trials; - Identifies and develops case report forms, program edit checks, and web logic specifications; - Drives innovation by integrating AI/ML capabilities into standard quality control processes; - Manages research protocols to include performing case-level reviews, queries, quality control review checks, and database lock activities. Qualifications - 8+ years of related experience preferred; - Bachelor’s degree in Life Science or BS degree or professional nursing degree/other healthcare certification required; - Supervisory experience preferred; - Experience developing EDC systems for clinical trials a plus; - Experience in a multi-modality clinical trials group or research team a plus; - Certified Medidata Rave® Study Builder, C#, and SAS programming experience a plus. Benefits - Competitive compensation and equitable pay; - Defined contribution pension plan; - 403(b) plan; - Generous paid time off package; - Insurance plans with leading providers; - Flexible spending; - Tuition reimbursement; - Training opportunities; - Wellness reimbursement. Company Description The American College of Radiology is a professional association serving over 40,000 members nationwide. The ACR’s Center for Research and Innovation (CRI) has been a world leader in radiology clinical research for over 50 years, conducting clinical research trials and other projects that have transformed the practice of radiology.
Qode is a unified hiring platform designed for enterprise scale, centralizing the entire hiring lifecycle in one environment. Key features include: Candidate sourcing and outreach. AI-led interviews in 30+ languages. Applicant tracking and job distribution to 200+ platforms. Outcome-based pricing: clients pay for results, not software seats. 800M+ candidate profiles indexed. 200,000+ applicants processed per month. 56+ enterprise clients worldwide.
Role Description - Experience: 8–10 years in Data Engineering and Data Analysis. - Informatica Expertise: Strong hands-on experience in Informatica PowerCenter/IDQ for ETL design, development, and optimization. - PySpark Development: Advanced skills in PySpark for large-scale data processing, transformation, and analytics. - Hadoop Ecosystem: Solid working knowledge of Hadoop technologies (HDFS, Hive, Sqoop, MapReduce). - Programming Skills: Proficiency in Python and Kafka for streaming and batch data pipelines. - Database & Modeling: Strong understanding of database concepts, data design, data modeling, and ETL workflows. - ETL Lifecycle: Experience in analyzing, designing, and coding ETL programs including data extraction, ingestion, quality checks, normalization, and loading. - Agile Delivery: Hands-on experience with Agile methodology and Jira for project delivery. - Client Interaction: Proven ability in client-facing roles with strong communication and leadership skills to coordinate across SDLC. Qualifications - Master’s or Bachelor’s degree in Computer Science or related field. - Strong problem-solving skills and ability to work in cross-functional teams. Requirements - Preferred Skills: - Exposure to AWS data components and analytics. - Familiarity with machine learning models and AI concepts. - Experience with data modeling tools such as Erwin.
K2United houses K2Share and CareerSafe, two brands with a common purpose to create solutions so those we serve thrive.
• The Senior Data Engineer will own the data engineering function on K2Share's Federal Team, partnering with technical and product leadership to deliver data products that support mission-critical decision-making for federal agency clients. • Design and build relational data layers that handle OSCAL and other structured compliance data - including ingestion, validation, transformation, and export workflows that preserve fidelity to source schemas across the full data lifecycle • Design and maintain data models that support governance, risk, compliance, scoring, and reporting workflows for federal cybersecurity programs, with OSCAL as the connective layer across them - including long-term retention and archival policies that align with federal recordkeeping and audit requirements • Design and build big-data processing pipelines on Databricks (PySpark, Delta Lake, Unity Catalog) that normalize cybersecurity data from across federal agency environments and produce analytical layers for trend analysis, executive reporting, and cross-program insights • Optimize data systems for performance and cost - identifying I/O and compute bottlenecks, scaling compute responsibly, and balancing throughput against the cost discipline federal engagements require • Architect, build and maintain AWS data infrastructure that meets federal security and operational requirements - working across services such as S3, Bedrock, Lambda, Fargate, and EC2 in support of compliance and analytical workloads • Design and implement audit-ready data primitives - change capture, access controls, validation, and lineage — that support agency reporting and continuous monitoring needs • Lead AI-first development and responsible AI deployment on the data team - using AI development tools as a standard part of the engineering loop, prototyping AI-assisted compliance workflows, and designing the production AI systems behind them (RAG architectures, vector store management, conversational agents, prompt and output guardrails, and evaluation pipelines), in alignment with federal AI governance guidance (OMB, NIST AI RMF) • Engage with federal agency stakeholders and internal teams during requirement discovery, delivery, and ongoing support — translating compliance needs into data products and customer feedback into improvements
MVB Bank is a community-focused financial institution headquartered in Fairmont, West Virginia, and operates as the primary subsidiary of MVB Financial Corp., a publicly traded fin
Role Description The Data Engineer position is responsible for designing, building, and maintaining robust data infrastructure and automation solutions that support our organization's data-driven initiatives. This role will work closely with cross-functional teams to develop scalable data pipelines, optimize data workflows, and ensure high-quality data delivery across the enterprise. This position requires strong technical expertise in Python and SQL programming, along with experience in modern data engineering tools and cloud platforms. What You’ll Do - Design, build, and maintain scalable data pipelines within Snowflake from multiple sources. - Build and maintain medallion architecture (bronze/silver/gold layers) for data lake solutions. - Design data models that support both business intelligence and AI requirements. - Lead cloud-native data platform evolution, integrating Snowflake with AWS. - Collaborate with business analysts, data scientists, and stakeholders to understand data requirements and translate them into technical specifications. - Implement data quality frameworks and monitoring systems to ensure accuracy, completeness, and consistency of data assets. - Develop and maintain comprehensive documentation for data pipelines, models, and processes. - Optimize query performance and resource utilization to reduce costs and improve processing times. - Participate in on-call rotation to support production data systems and resolve incidents. Qualifications - Bachelor's degree in Computer Science, Information Systems, Data Engineering, Mathematics, Statistics, or related technical field or equivalent relevant experience required. - 5+ years of hands-on data engineering experience building production-scale data systems. - Snowflake proficiency: warehouses, databases, roles, RBAC, Snowpipe, streams, tasks, and performance optimization. - Strong SQL mastery: complex queries, window functions, CTEs, query optimization, and database design. - Programming proficiency: Python for data transformation, automation, and pipeline development. - Cloud platform experience: Deep knowledge of AWS data services and architecture patterns. - Version control and CI/CD: Git, GitHub/GitLab, automated testing, and deployment pipelines. - Orchestration expertise: Apache Airflow or similar workflow management tools. - Excellent communication skills with ability to explain technical concepts to non-technical stakeholders. - Experience in financial services or highly regulated industries preferred. - Familiarity with data governance tools and frameworks preferred. - Experience with Snowflake engineering processes preferred. - Certifications: Snowflake SnowPro Core and AWS Cloud practitioner preferred. - Understanding of business intelligence, machine learning workflows, and AI practices preferred. Benefits - Medical, Dental and Vision Insurance. - Health Savings Account (HSA), Health Reimbursement Account (HRA) & Flexible Spending Accounts (FSA). - Short- and Long-Term Disability Plan. - Group Life Insurance. - 401K Salary Deferral Plan. - Wellness Program. - Education & Tuition Expense Reimbursement. - PTO and Unique Vacation Purchase Program. - Nationwide Pet Insurance Coverage.
Empowering Manufacturing Innovation through Engineering Excellence and Tailored Solutions
• Evaluate and improve data quality, completeness, and consistency across 30+ databases, applications, platforms, and APIs. • Design and build Scorpion's analytical data platform, creating a trusted source of truth for business and client data. • Develop and maintain scalable data pipelines that efficiently move data from operational systems into the analytical platform. • Help teams transition from querying production databases directly to using trusted analytical data sources. • Design data access patterns that enable AI agents and applications to quickly retrieve relevant client and business information. • Build secure, scalable solutions that deliver client context and business insights to internal applications and AI-powered experiences. • Define, monitor, and improve service level agreements (SLAs) for data freshness, availability, reliability, and performance. • Partner with engineering, product, and data science teams to establish data standards, governance practices, and data contracts. • Continuously improve the scalability, performance, and reliability of Scorpion's data ecosystem.
• Design, build, and operate ETL/ELT pipelines from operational and SaaS sources • Develop batch and streaming workflows using Python, SQL, and cloud data services • Model data in a warehouse/lakehouse (e.g. Snowflake, Databricks, or BigQuery) • Implement data quality checks, monitoring, and incident response for pipelines • Collaborate with analysts and data scientists on curated marts and metrics • Document pipelines, schemas, and SLAs; support CI/CD for data code • Optimize performance, cost, and security (IAM, encryption, PII handling)
Headquartered in Oakland, California, Marqeta created an open application programming interface (API) to help simplify the way payment programs are managed. The
• The lakehouse and the streaming ingestion that feeds it. • You’d help set the multi-year technical direction, design the golden paths, and ship the work — directly, with your hands on the code that matters. • You’d report to the Director of Data Engineering and partner with a peer Manager whose scope is people leadership and operational delivery. • You own technical direction, application architecture, and the engineering bar. • You’ll work alongside other senior staff engineers across the broader data platform org.
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Python, ETL, SQL, AI/ML, AWS, AI
