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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Platform Solutions Lead - **Company:** Capital Integration Systems LLC - **Location:** New York, NY, United States - **Experience:** Expert - **Salary:** $170,000.0 - $200,000.0 - **Contract:** Permanent contract - **Skills:** Adaptable Database Systems, Artificial Intelligence, Data Architecture, Information Engineering, Data Governance, Dataspaces, Data Systems, Data Visualization, Data Warehousing, Digital Assets, Document-Oriented Databases, Software Architecture, Raw Data, SQL Databases, Tableau (Software), Snowflake, Collibra, Data Pipelines - **Published:** August 22, 2026 - **Apply:** https://www.dice.com/job-detail/15a90f58-fefd-4d97-bf42-291d03b94a72 ## About the Role * Demonstrated experience applying AI tools in a data context - including data governance, data modeling, or pipeline development with a track record of leveraging AI to drive efficiency and better outcomes. * Experience in data engineering, analytics engineering, or a data architecture role, ideally within financial services or fintech. * Strong proficiency in SQL and experience with Snowflake for data warehousing and transformation. * Hands-on experience with dbt for data modeling and workflow management. * Working knowledge of data governance concepts and tooling; experience with platforms like DataHub, Collibra or Alation is a plus. * Demonstrated ability to build internal tools or data products that solve practical business problems. * Strong communication skills with the ability to engage both technical and non-technical stakeholders. Highly Advantageous Skills * Familiarity with Python for data processing or automation. * Experience with BI and data visualization tools such as Tableau. ## Description * Design and implement scalable data models that structure raw data into clean, well-documented assets powering analytics, reporting, and downstream applications. * Own and drive CAIS's data governance initiatives, including defining data ownership, establishing quality standards, and maintaining a well-cataloged and discoverable data environment. Partner with the Data Engineering team to ensure governed data assets are structured and ready for downstream integration. * Actively leverage AI tools across all aspects of your work - from data modeling and governance to documentation, exploratory analysis, and tool development. * Contribute to and guide the development of internal tools and data products that improve how teams across the firm access and act on data - including AI-assisted workflows and automation. * Ensure data assets are structured, governed, and well-documented to support AI and machine learning use cases, serving as a key enabler of the firm's AI initiatives. * Define and enforce data quality checks, identify inconsistencies, and drive resolution across pipelines. * Partner with business and technical stakeholders to translate requirements into practical data solutions. * Document data assets, business definitions, and architectural decisions to support a shared understanding of the data ecosystem. ## Related Videos - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Data Governance in the Era of AI](https://www.wearedevelopers.com/videos/1622-data-governance-in-the-era-of-ai) - [How Cisco embraced a DevOps culture within its network engineering team](https://www.wearedevelopers.com/videos/99-how-cisco-embraced-a-devops-culture-within-its-network-engineering-team) - [Bringing Clarity to Event Streams: Enabling Analytics and AI Through Rich Metadata](https://www.wearedevelopers.com/videos/1616-bringing-clarity-to-event-streams-enabling-analytics-and-ai-through-rich-metadata) - [Hacking AI at the Edge of the Indian Ocean](https://www.wearedevelopers.com/videos/100177-hacking-ai-at-the-edge-of-the-indian-ocean) - [Modern Data Architectures need Software Engineering](https://www.wearedevelopers.com/videos/1030-modern-data-architectures-need-software-engineering) ## Related Articles - [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [Top Big Data Technologies That You Need to Know](https://www.wearedevelopers.com/magazine/108-top-big-data-technologies-that-you-need-to-know) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [Stephan Gillich - Bringing AI Everywhere](https://www.wearedevelopers.com/magazine/489-stephan-gillich-bringing-ai-everywhere) - [Graph and AI Trends 2026: Why Is AI Running but Not Yet Delivering?](https://www.wearedevelopers.com/magazine/680-graph-and-ai-trends-2026-why-is-ai-running-but-not-yet-delivering)