Role Description Vantaca IQ is the intelligence layer at the core of Vantaca’s platform, and this team builds it. You take messy, multi-tenant operational data, organize it, and turn it into the insights and signals the platform acts on — surfaced where decisions get made and served to HOAi agents that act on it. You own the stack that makes that possible: - Ingestion and pipelines - Schemas and aggregation beneath every report - Reporting and ad-hoc query surfaces - Derived-intelligence layer - Semantic and ontological model on top IQ is data-as-a-service, one governed source feeding humans and agents where they are — proactive, personalized, channel-agnostic. The hard problems sit here: - Serving cross-tenant data without leaking a byte - Semantic governance that keeps one number from forking into five - Eval harnesses that prove a grounded LLM is right - Pipelines trustworthy enough to bill against and report to boards What the Team Owns - Ingestion & pipelines: batch and change-data-capture out of the operational system of record; transformations, scheduling, backfills, and idempotent reprocessing. - Data models & metric layer: relational and dimensional schemas, and define-once metrics with thoughtful governance. - Aggregation, rollups & derived metrics: materializations, incremental rollups, and partitioning/indexing for fast, cheap queries — plus the score and benchmark jobs, with data-quality checks, lineage, and tests that keep them correct. - Multi-tenant isolation: tenant-scoped access and row/column controls on every surface, including cross-tenant aggregates that expose no individual tenant's data. - Access & serving layer: how every consumer reads the platform's intelligence — query and metrics APIs, an MCP server for agents and external tools, embeddable feeds, and push to Teams and Slack — one governed contract whether the caller is a person, an app, or an agent. - Reporting & ad-hoc surfaces: report definitions, board-packet generation, and self-serve query interfaces. - LLM grounding & evals: the retrieval/semantic interface an LLM queries against, and the eval harnesses that measure and gate accuracy. - Signal & action contracts: insight-detection jobs and the typed, audited output contracts HOAi agents consume to act. What We're Looking For - Data fundamentals: you've built pipelines or aggregation layers over messy operational data and understand how analytical engines execute your queries. - Modeling instinct: relational and dimensional modeling, and the conviction that every metric you publish is an interface someone, or some agent, depends on. - Product sense for data: you care that an insight changes how our users do business. - AI-native by default: Active daily use of AI coding agents (Claude Code, Cursor, or similar); this is a baseline, not a differentiator. - Polyglot and pragmatic: You reach for the right tool to solve each problem, while thoughtfully evolving the ecosystem. - Curiosity and ownership: you run at ambiguous problems and take systems end-to-end (build → ship → operate). - Source-of-truth scar tissue: you've built a data platform other teams trusted and kept it trustworthy as it grew. - Semantic governance: you've defined semantic-layer or metric-governance architecture and lived with the consequences. - Grounded-LLM receipts: you've shipped or evaluated an LLM system grounded in governed data and can explain what you measured. - Raising the bar: testing strategy, documentation, and mentoring. Nice to Have - Semantic-layer or metrics-store experience (e.g., MetricFlow, LookML, Cube, dbt, or similar). - Modern data stack exposure (e.g., warehouses, lakehouses, event streaming, and orchestration tools). - Multi-tenant analytics or cross-customer benchmarking — serving derived intelligence without leaking anyone's data. - Exposure to property management, HOA, or real estate tech — helpful but not required. Core Values - Always Growing: Likes change and enjoys finding new ways to improve their knowledge and the platform. Always ready to learn quickly about emerging AI technologies and infrastructure patterns, helping themselves and the team grow. - Win as a Team: Builds trust and works together by making sure everyone communicates well. Actively involved in daily platform work, working closely with engineering teams, listening to their infrastructure needs, and celebrating technical successes together. - Accountability Starts with Me: Notices platform problems and takes personal action to solve them. Takes ownership of platform performance, reliability, and the success of internal customers building on the platform. - Unwavering Commitment to Customer Experience: Regularly talks to internal customers (product teams, engineers), taking personal responsibility to understand what they need from the platform, address infrastructure concerns, and make their development experience better with improved platform capabilities. - Innovate Boldly: We challenge the status quo and push technical boundaries to create meaningful change. We act with urgency and purpose, knowing that platform innovation drives our AI-native product success. Benefits - Medical, Dental, and Vision kick in day one - Unlimited PTO (with a requirement for employees to take a minimum of one continuous week per year) - 401K with Company Match - Remote Flexible - come to the office when needed - Great parental leave benefits - Named on Inc 5000 list of America's Fastest Growing Private Companies - Named on Inc 5000 Vet 100 Private Companies list multiple years in a row - Winner of Coastal Entrepreneur Award, Technology Category - Active employee-led Culture Committee - Ongoing industry and professional development trainings available to all employees - Multiple leaders on the executive committee recognized as 40 under 40 recipients for contributions to business and community Why You Should Join Our Team - AI-First Product Culture - Build the intelligent infrastructure that powers AI innovation at scale - Our eNPS is +68! (Google it, that is great)

Role Description We are sharing a specialised remote consulting opportunity for experienced data engineers with strong coding agent experience, practical data infrastructure judgment, and the ability to evaluate complex data engineering implementations across realistic technical scenarios. This role supports current and upcoming remote consulting opportunities focused on data engineering evaluation, coding-agent-assisted technical workflows, pipeline assessment, data platform review, and distributed data system analysis. Selected professionals may use tools such as Cursor, Claude Code, Codex, Windsurf, Gemini CLI, or comparable coding agents to complete, review, and evaluate data engineering tasks involving ETL pipelines, data warehouses, analytics platforms, distributed systems, and large-scale data infrastructure. Key Responsibilities - Data Engineering Evaluation - Use modern coding agents to complete and evaluate complex data engineering tasks - Review generated implementations involving ETL pipelines, data warehouses, analytics platforms, and distributed data systems - Assess technical outputs for correctness, scalability, maintainability, reliability, and production-readiness - Apply professional data engineering judgment to realistic infrastructure and pipeline scenarios - Pipeline & Data Platform Review - Evaluate pipeline architecture, data transformation logic, ingestion workflows, orchestration patterns, and data quality checks - Review data warehouse and analytics platform implementations for performance, accuracy, structure, and maintainability - Identify bugs, edge cases, scalability issues, failure modes, and weak assumptions in data engineering outputs - Provide structured feedback on data flow, system design, reliability, and implementation quality - Coding Agent Output Assessment - Compare outputs from multiple coding agents and assess their strengths, weaknesses, accuracy, and practical usefulness - Identify where generated solutions succeed, where they fail, and where additional engineering judgment is required - Evaluate whether generated data infrastructure reflects real-world data engineering standards - Document technical review findings clearly for project teams and quality evaluation workflows - Technical Documentation & Feedback - Produce clear, structured evaluations of data engineering tasks and generated outputs - Explain reasoning around pipeline design, data modelling, warehouse architecture, distributed systems, scalability, and failure handling - Support technical assessment workflows by documenting accepted work, improvement areas, and practical engineering conclusions - Help ensure outputs reflect production-scale data engineering expectations Qualifications - 2+ years of professional data engineering experience - Hands-on experience building ETL pipelines, data warehouses, analytics platforms, distributed data systems, or large-scale data infrastructure - Regular use of AI coding agents such as Cursor, Claude Code, Codex, Windsurf, Gemini CLI, or comparable tools - Ability to evaluate generated data infrastructure and pipeline implementations for correctness, scalability, and reliability - Experience supporting large-scale data platforms is strongly preferred - Strong understanding of data modelling, data quality, orchestration, distributed processing, warehouse design, and pipeline maintainability - Clear written communication skills and comfort documenting technical reasoning in a remote, project-based environment Educational Background - A degree in Computer Science, Data Engineering, Software Engineering, Computer Engineering, Information Systems, Statistics, or a related technical field is helpful - Equivalent professional experience in data engineering, analytics engineering, distributed systems, or production data platforms is also highly relevant Nice to Have - Experience with Python, SQL, Spark, Airflow, dbt, Kafka, Flink, Snowflake, BigQuery, Redshift, Databricks, or comparable data tools - Familiarity with cloud data platforms, data lakehouse architecture, orchestration systems, batch processing, streaming pipelines, or data quality frameworks - Experience with CI/CD workflows, Docker, Kubernetes, Terraform, observability tooling, or infrastructure automation in data environments - Background in technical code review, data architecture review, pipeline performance evaluation, or large-scale analytics systems - Strong comfort working in sprint-based project environments with focused technical assessment windows Why This Opportunity - Remote consulting work aligned with data engineering, coding agent, and technical evaluation expertise - Opportunity to evaluate realistic data engineering workflows involving ETL pipelines, data warehouses, analytics platforms, and distributed data systems - Suitable for engineers who enjoy technical assessment, tool-assisted coding workflows, pipeline review, and practical data infrastructure problem-solving - Sprint-based project work that can align with focused availability and remote schedules Contract Details - Independent contractor engagement - Fully remote and flexible scheduling - Sprint-based, project-based availability - Some project work may run in focused 12–24 hour sprint windows depending on project requirements - Compensation may reach up to $90/hour, depending on project scope, experience, and accepted work structure - Some projects may use accepted-task compensation depending on the specific workflow - Payments are made weekly via Stripe or Wise based on services rendered - Projects may be extended, shortened, adjusted, or concluded based on project needs and performance - Candidates requiring H1-B or STEM OPT sponsorship support are not eligible at this time - Work must not involve sharing confidential or proprietary information from any employer, client, or institution About the Platform This opportunity is available through 24-MAG LLC. We connect experienced professionals with remote consulting opportunities across technical, evaluation, and project-based workstreams. By submitting this application, you acknowledge that your information may be processed by 24-MAG LLC for recruitment and opportunity matching in accordance with our Privacy Policy: https://www.24-mag.com/privacy-policy

Role Description At Cotiviti, we are custodians of data for our clients. Using their technical experience in ETL processes, Data Engineers ensure operational functions are occurring as expected. This includes but is not limited to managing data implementations, data integrations, data production, data quality, and data security. - Create, maintain and execute intermediate to advanced Spark scripts for data management, validation, and integration. - Create, maintain and execute basic to intermediate SQL scripts for data management and validation. - Optimize the queries to improve the efficiency of daily tasks. - Perform data analysis and identify any issues. - Work with other groups such as Engineering team, DBA, Cloud ops, etc. to troubleshoot and resolve any environmental or network issues that impact your work. - Extend support to after-hours or weekends as needed. - Create and maintain data pipelines as needed. - Validate task results to ensure that all requirements are met. - Adhere to all industry-level and organization-level compliance rules and regulations to maintain data integrity. - Complete individual productivity tracking. - Complete task assignments using department ticketing system within assigned deadline. - Achieve organizational and individual goals as identified in performance reviews and goal-setting exercises. - Complete all special projects and other duties as assigned. - Must be able to perform duties with or without reasonable accommodation. Qualifications - Bachelor’s degree in Computer Science, Information Technology or equivalent work experience. - 3+ years of working knowledge of big data technologies (Spark, S3, Kafka, Ray, Hadoop, etc.). - 2+ years of working knowledge of big data / cloud technologies (Databricks, AWS, Azure, Hadoop, Spark, Snowflake etc.). - 3+ years of working knowledge of cloud (AWS, Azure, GCP, OCI etc.). - 3+ years of working knowledge of RDBMS (Oracle, MS SQL, Vertica, etc.) and experience using SQL, PL/SQL or other data integration/ETL tools. - Any Databricks / AWS certifications is a big plus. - Familiarity with data pipeline orchestration tools (e.g., Airflow, Databricks Workflows). - 3+ years of data analysis, preferably in the Healthcare industry of enrollment, medical claims and/or pharmacy claims. - Proficient in Microsoft Office Suite applications PowerPoint, Word, Excel and Outlook. - Flexible work schedule. - Experience with project management tools like JIRA. - Databricks and/or Snowflake environment familiarity a plus. Requirements - Strong analytical skills. - Excellent verbal, listening and written communication skills. - Ability to multitask and prioritize projects to meet scheduled deadlines and tight turnaround times. - Ability to work well independently or in a team environment. Working Conditions and Physical Requirements - Remaining in a stationary position, often standing or sitting for prolonged periods. - Repeating motions that may include the wrists, hands, and/or fingers. - Must be able to provide a dedicated, secure work area. - Must be able to provide high-speed internet access/connectivity and office setup and maintenance. Benefits - Base compensation ranges from $101,000 to $132,000 per year. - Cotiviti offers a competitive benefits package including: - Medical, dental, vision, disability, and life insurance coverage. - 401(k) savings plans. - Paid family leave. - 9 paid holidays per year. - 17-27 days of Paid Time Off (PTO) per year, depending on specific level and length of service with Cotiviti. Company Description Since this job will be based remotely, all interviews will be conducted virtually. Date of posting: 5/7/2026 Applications are assessed on a rolling basis. We anticipate that the application window will close on 8/7/2026, but the application window may change depending on the volume of applications received or close immediately if a qualified candidate is selected. #LI-REMOTE #LI-LL1 #SENIOR

Role Description The Enterprise Data Architect and Technical Lead is a strategic and hands-on leadership role within the Enterprise Information Management (EIM) team. This position is responsible for defining and driving the enterprise data architecture vision for scalable, high-quality data solutions. The role combines deep expertise in data modeling, middleware, MDM, and visualization with the ability to lead through influence—collaborating closely with ETL developers, data engineers, and BI developers across a multidisciplinary environment to drive outcomes. The successful candidate will oversee the design and implementation of the Enterprise Data Warehouse – inclusive of data products (EDW), enterprise integration layer (ie, middleware), MDM, and ensuring that data platforms are aligned with business objectives, optimized for performance, and governed by best practices. This role will also guide the technical execution of data projects, manage resource allocation, and foster collaboration across functional and IT teams. Qualifications - Bachelor's degree in Computer Science, Information Systems, Engineering, Business, or a related field or equivalent experience in a technical or business discipline. - 10-15 years’ experience with the following tools and concepts: - Databases such as SQL Server / Oracle - ETL or Middleware software such as Informatica, Mulesoft - Columnar databases such as Snowflake / Vertica - Data Modeling tools such as ERWin or ER Studio - Processing large volumes of structured and unstructured data - Data movement and transformation technologies - Version Control software such as TFS, CVS or GIT (preferred) - Strong analytics skills - Strong written and verbal communication skills - Sound business and technical acumen - Strong time management, organization, and execution skills - Ability and desire to work in a fast-paced, dynamic environment - Strong collaboration skills required to effectively work across a diverse group including executives, managers, and subject matter experts - Self-starter who takes initiative to get tasks done Requirements - Prior experience in the following areas is highly desirable: - SAP functional modules (Finance/Accounting, Supply Chain, Materials Management, Warehouse Management, Procure to Pay) - Delivering BI / DW solutions to end users in the pharmaceutical industry - Demonstrated capabilities (e.g. able to translate strategy to action, effective verbal and/or written communication at all levels of organization, work effectively in ambiguous situations, ability to multi-task, proven track record of increasing customer base) Benefits - The estimated annual base salary as a new hire for this position ranges from $155,500 to $188,200. - Individual base pay depends on various factors such as applicant’s education, experience, skills, and abilities, as well as internal equity and alignment with market data. - The salary may also be adjusted based on applicant’s geographic location. - Certain roles are eligible for additional incentive compensation, including merit increases, annual bonus, and/or long-term incentives in the form of stock options. - Emergent offers a comprehensive benefits package.