[![Image]() Meet Jobicy Copilot — free AI autofill for job applications + remote job alerts ›](#) [All remote jobs](https://jobicy.com/jobs.md)Open role[![Tala logo](https://jobicy.com/data/server-nyc0409/galaxy/mercury/2022/02/a788b3a65c0fc717303f0b5b049cc7e6.jpeg)](https://jobicy.com/company/tala.md)Remote opportunity at[Tala](https://jobicy.com/company/tala.md) # Analytics Platforms Architect Review the role, location requirements, compensation details, and application process before deciding whether this opportunity fits your next career move. [Apply for this job](#job-application)[View company](https://jobicy.com/company/tala.md)Share16 Sep 2026Published48Listing views3Application actions16 Oct 2026Apply before Opportunity details ## About this role. AI SummaryTala seeks a Principal/Staff-level individual contributor to architect and build shared analytics and data-platform capabilities. The role centers on a governed semantic layer, trusted business metrics, production data models and pipelines, and reusable tooling for BI, applications, notebooks, and AI agents. This architect will lead cross-functional technical initiatives spanning Product, Engineering, Analytics, Finance, and Accounting while remaining highly hands-on in code and delivery. Success requires strong data architecture judgment, influence without formal authority, and the ability to turn ambiguous platform needs into reliable, scalable systems. ## Role DNA A quick view of the complexity, pace, ownership and collaboration implied by the job description. ### Job Complexity 5/5EasyHard ### Pace & Pressure 4/5RelaxedFast-paced ### Autonomy Level 5/5GuidedFull ownership ### Communication Load 5/5IndependentCollaborative AI insightThis is a senior technical leadership role requiring ownership of enterprise-wide data architecture while also delivering production systems. The architect must reconcile governance, reliability, financial accuracy, AI enablement, and the needs of diverse stakeholders across a global fintech environment. ## Salary analysis Estimated compensation compared with the broader US market for similar roles. Estimated job medianMarket rate$180,000US market range$160k–$220k0$242k AI insightThe disclosed yearly base compensation range is USD 160,000 to 200,000, with a midpoint of USD 180,000. A competitive US market range for a Principal/Staff-level analytics platform or data architecture role is estimated at USD 160,000 to 220,000 annually; actual total compensation may vary based on location, scope, equity, and experience. ## Core skills Skills and capabilities most closely associated with this opportunity. [Data architecture](https://jobicy.com/jobs?search_keywords=Data%20architecture.md)[Analytics platforms](https://jobicy.com/jobs?search_keywords=Analytics%20platforms.md)[Semantic layer](https://jobicy.com/jobs?search_keywords=Semantic%20layer.md)[Data modeling](https://jobicy.com/jobs?search_keywords=Data%20modeling.md)[Data pipelines](https://jobicy.com/jobs?search_keywords=Data%20pipelines.md)[Analytics engineering](https://jobicy.com/jobs?search_keywords=Analytics%20engineering.md)[AI/LLM workflows](https://jobicy.com/jobs?search_keywords=AILLM%20workflows.md)[Data governance](https://jobicy.com/jobs?search_keywords=Data%20governance.md)[Financial data reconciliation](https://jobicy.com/jobs?search_keywords=Financial%20data%20reconciliation.md)[Technical leadership](https://jobicy.com/jobs?search_keywords=Technical%20leadership.md) Sample interview questionsHow would you design a semantic layer that provides consistent business metrics across BI tools, notebooks, applications, and AI agents?I would begin by identifying high-value metrics, their owners, source systems, grain, dimensions, and reconciliation requirements. I would implement version-controlled metric definitions and governed data models with clear lineage, testing, access controls, and documentation. The semantic layer would expose stable interfaces for each consumption channel, while observability and change-management processes would ensure definitions remain trustworthy over time. Describe how you balance hands-on delivery with setting long-term architecture direction in a Staff or Principal role. I translate architecture into a sequenced roadmap of concrete platform capabilities, then personally own critical paths or high-risk components to validate decisions in production. I use design reviews, reference implementations, pairing, and reusable standards to raise the broader team's capability. This keeps the strategy grounded in operational realities while allowing other engineers to deliver consistently. How would you ensure that financial and business metrics reconcile with Finance and Accounting reporting? I would establish a shared metric contract with Finance and Accounting that defines authoritative sources, calculation logic, cut-off rules, currency treatment, and acceptable reconciliation tolerances. Automated tests would compare analytics outputs with accounting reports at agreed reporting periods, with exception workflows for investigation. Clear lineage and ownership would make discrepancies auditable and prevent multiple teams from maintaining competing definitions. What governance controls would you implement before allowing AI agents to work with company data and metrics? I would enforce role-based access, data classification, approved semantic contexts, and policy-aware retrieval so agents only receive authorized and trusted inputs. I would also require audit logs, prompt and output monitoring, evaluation suites, human review for sensitive workflows, and safeguards against exposing regulated or personally identifiable data. The rollout would start with constrained use cases and expand only after reliability and security thresholds are met. Tell us about your approach to leading a cross-functional initiative when you have no direct authority over contributors. I create alignment by making the business outcome, technical trade-offs, decision owners, dependencies, and delivery milestones explicit. I involve stakeholders early, use evidence and prototypes to resolve disagreement, and communicate progress and risks in language appropriate to each audience. When blockers arise, I drive decisions to closure while ensuring teams understand how the work advances their own goals. About Tala Tala is AI-native credit infrastructure for the global majority, combining proprietary risk intelligence with an expanding network of capital and distribution partners to power credit access at scale. Backed by more than $500 million in funding, Tala has distributed more than $7 billion in capital to more than 13 million customers across Africa, Latin America, and Asia—building one of the most robust datasets on thin-file borrowers anywhere in the world. Our mission is simple yet bold: to unleash the economic power of the global majority. We are looking for daring, data-driven leaders passionate about building the trust and credit infrastructure for the global majority. Our pioneering work and proven impact have earned us consistent recognition, including being named to: CNBC’s Disruptor 50 for five years. CNBC’s World’s Top Fintech Companies for two consecutive years. Forbes’ Fintech 50 list for nine consecutive years. Visionary investors, persuaded by the economic power of the global majority, have committed half a billion dollars in equity and debt to Tala’s success. Given the global nature of our team, we operate on a remote-first approach with office hubs in Santa Monica, CA (HQ); Nairobi, Kenya; Mexico City, Mexico; Manila, the Philippines; and Bangalore, India. Most Talazens join us because they connect with our mission. If you are energized by the impact you can make at Tala, we’d love to hear from you! The Role We’re looking for an Analytics Platforms Architect to be the senior technical leader responsible for making Tala’s data easier to trust, understand, access, and use across the company. This is a highly hands-on technical leadership role. You’ll define the architecture and technical direction for shared data and analytics platforms while also building alongside our engineers. You’ll work across Product, Analytics, Engineering, Finance, and Accounting to create infrastructure that becomes the foundation for how Tala uses data. A major focus will be building a semantic layer that gives the organization consistent, governed definitions for important business metrics. You’ll also help establish how our analytics teams and AI tools safely work with that data. This isn’t an architecture role where you simply create designs and hand them off to someone else. You’ll be expected to make technical decisions, write code, build production systems, and drive important platform initiatives through delivery. Initially, this role is an individual contributor position with no direct reports, operating at a Principal/Staff-level scope. As our platform organization grows, there will be an opportunity to build and lead a team. ### What You’ll Do: Own Data Platform Architecture * Define the technical architecture for Tala’s semantic layer and shared analytics platform. * Establish consistent, governed definitions for business metrics across markets and teams. * Determine how data and metrics should be stored, modeled, accessed, and consumed across BI tools, notebooks, applications, and AI agents. * Make architectural decisions that balance scalability, reliability, usability, governance, and regulatory requirements. * Set technical priorities and sequencing for major platform initiatives and ensure they reach completion. Build, Don’t Just Architect * Design and build production data models, pipelines, services, tooling, SDKs, and other platform components. * Partner closely with Analytics Engineering and Data Infrastructure as a senior technical contributor. * Take ownership of specific platform capabilities from concept through production. * Identify and eliminate technical debt and architectural bottlenecks that slow down the broader data organization. * Establish reusable patterns and standards that make it easier for engineers and analysts to work with data. Build AI-Native Analytics * Define how Tala’s Analytics organization can effectively use AI in everyday workflows, including development, analysis, testing, documentation, and data exploration. * Build the context and governance layer that enables AI agents to safely work with trusted business metrics and data. * Establish standards and best practices for using AI across analytics and data workflows. * Help move AI initiatives from experimentation and prototypes into reliable, adopted tools and processes. Drive Cross-Functional Data Initiatives * Lead technical initiatives that span Product, Engineering, Analytics, Finance, and Accounting. * Bring clarity to ambiguous problems and drive technical decisions to completion. * Unblock engineers and teams by resolving dependencies, architectural questions, and technical debt. * Partner with Finance and Accounting to ensure important financial and business metrics reconcile with the company’s books and reporting. * Build strong relationships across teams and influence technical decisions without relying on formal authority. Raise the Technical Bar * Provide technical mentorship through design reviews, pairing, and hands-on collaboration. * Establish engineering and data architecture standards. * Improve documentation and make data easier for teams to understand and use. * Help create a culture where governance, reliability, and usability are built into data products from the beginning. ### What You’ll Need: * Significant experience in data engineering, software engineering, analytics engineering, data platforms, or a related technical field. * Experience designing and building large-scale or shared data platforms and infrastructure. * Strong experience with data architecture, data modeling, pipelines, and production systems. * A track record of making complex architectural decisions and translating them into working systems. * The ability and willingness to write production code and build alongside engineers. * Experience leading technical initiatives across multiple teams without necessarily having direct authority over those teams. * Strong problem-solving skills and the ability to bring ambiguous or stalled initiatives to completion. * Experience establishing trusted, governed, or standardized business metrics is highly valuable. * Experience with AI/LLM-powered analytics, data workflows, or agents is a strong plus. * Experience working with financial, regulated, or highly sensitive data is a plus. * Excellent communication skills and the ability to explain complex technical concepts to both technical and non-technical stakeholders. ### Compensation ### Additional Information Our vision is to build a new financial ecosystem where everyone can participate on equal footing and access the tools they need to be financially healthy. We strongly believe that inclusion fosters innovation and we’re proud to have a diverse global team that represents a multitude of backgrounds, cultures, and experience. We hire talented people regardless of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, or disability status. 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