Data Platform Engineer

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Typeform

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B2B • SaaS • Productivity

Typeform is a versatile online form builder that enables businesses to create forms, surveys, and quizzes that are engaging and easy to use. With a focus on delivering a superior user experience, Typeform designs forms that break the mold by using branded designs, video content, and dynamic questioning that adapts based on previous answers. Ideal for B2B marketers, Typeform not only facilitates data collection but also offers AI analysis to derive insights from customer data, helping businesses make more informed decisions. Typeform integrates seamlessly with numerous apps, providing robust and dynamic solutions for marketing, research, human resources, and customer success teams.

201 - 500 employees

Founded 2012

🤝 B2B

☁️ SaaS

⚡ Productivity

📋 Description

• Serve as the technical authority for data platform and tracking architecture—guiding design decisions, tool selection, and engineering best practices. • Design a next-generation data & AI platform that supports near-real-time ingestion, enrichment, and model-driven product features. • Translate AI Engineering requirements into clear specifications and capability roadmaps through spec-driven development. • Define and implement modern data governance: data quality, lineage, ownership, observability, and cost visibility. • Evaluate, consolidate, or replace redundant technologies, introducing scalable SaaS solutions where appropriate. • Own and extend core AI-platform components, including: Arize AI (evals & observability), LLM Gateway (model routing, policies, cost controls), Pinecone (vector database), Model access APIs, OTEL collector for trace processing. • Take full ownership of the AI Infrastructure components currently run by AI Engineering—ensuring reliability, scale, and clear fallback strategies. • Document existing workflows across Analytics Engineering, Data Engineering, and AI Engineering to identify automation and process improvements. • Introduce streamlined development pathways for AI—templates for CI/CD, GitOps, Python microservices, and AI-specific libraries. • Implement FinOps principles: baseline costs, identify inefficiencies, and reduce spend across data and AI workloads. • Support the transition toward a more self-serve model through ADRs, RFCs, and well-defined ownership guidelines. • Mentor Data Engineers on modern Data Platform concepts—streaming, governance, observability, platform reliability, and AI-aligned workflows. • Partner with Platform Engineering, TechOps, Data Science, and AI Engineering to drive alignment and cohesive infrastructure strategy. • Define playbooks and guidelines that standardize how teams build pipelines, collaborate with Platform, and deliver AI-ready data. • Increase trust across the organization through clear documentation, architecture records, and consistent communication.

🎯 Requirements

• Several years of experience as a software engineer or platform engineer working with large-scale data systems, streaming architectures, or data/AI platforms. • Proven experience designing and delivering data platforms, including real-time ingestion, enrichment, data warehousing, and lake/lakehouse architectures. • Expertise with streaming technologies (Kafka or similar), reverse-ETL, and modern big-data tooling. • Hands-on experience with platform components such as Terraform, Terragrunt, CI/CD pipelines, Python, SQL, and cloud-native infrastructure. • Experience partnering with Data Science, AI Engineering, and cross-functional teams to translate requirements into scalable platform capabilities. • Strong communicator with the ability to influence stakeholders and document architecture clearly. • Experience mentoring, coaching, or leading engineers technically (even without direct reporting lines)

🏖️ Benefits

• Health insurance • 401(k) matching • Flexible work hours • Paid time off • Remote work options