Senior AI-First Data Engineer

As a Senior AI-First Data Engineer, you will be responsible for designing, evolving, and scaling modern data infrastructure while enabling AI-powered business capabilities.

Build and evolve a scalable, cloud-native data platform that supports AI applications, analytics, automation, and business operations.

Lead the transition from traditional batch processing architectures toward near real-time and streaming data systems.

Improve data platform reliability, observability, governance, security, and performance through engineering best practices.

Develop data products and foundations that allow AI agents, analytics systems, and business users to access and leverage trusted information.

Create semantic layers, metadata structures, and knowledge frameworks that make data more discoverable and actionable.

Enable AI-driven reporting, forecasting, and business intelligence capabilities by transforming static analytics into dynamic operational systems.

Use AI tools to accelerate engineering workflows, including development, testing, documentation, debugging, and monitoring.

Design systems that allow AI agents to safely query, understand, and interact with business data.

Evaluate emerging AI technologies and identify opportunities to improve productivity across data teams.

Improve accessibility and adoption of BI solutions while maintaining strong governance and data quality standards.

Provide technical leadership through architecture guidance, code reviews, mentorship, and knowledge sharing.

Partner with engineering, product, analytics, and business stakeholders to align technical investments with strategic goals.

The ideal candidate is an experienced data engineering professional with a strong background in building scalable platforms and applying AI-driven approaches to modern data workflows.

6+ years of experience in data engineering, analytics engineering, or a related technical field.

Proven experience designing, implementing, and operating modern cloud-based data platforms.

Experience working in high-growth SaaS or technology environments.

Strong ability to manage complex projects from technical design through successful delivery.

Experience collaborating with both technical teams and business stakeholders.

Hands-on expertise with Databricks, dbt, Airflow, Python for data engineering, SQL, and data modeling.

Strong understanding of data warehousing architectures, orchestration, integration, quality frameworks, and governance practices.

Experience with streaming architectures, event-driven systems, BI platforms, product analytics tools, CRM data platforms, or customer data platforms.

Demonstrated AI-first mindset, including experience using AI-powered development workflows and automation tools.

Ability to leverage AI for debugging, testing, documentation, architecture exploration, and productivity improvements.

Curiosity about agentic systems and experience integrating AI into data or analytics workflows.

Nice-to-have experience with AI-native data products, semantic layers, RAG systems, vector databases, knowledge graphs, or enabling AI agents to consume operational data.

Remote-friendly working environment with flexibility to work from locations where you perform best.

Opportunity to join a globally distributed team across multiple countries and cultures.

Chance to contribute to the development of an AI-native organization and shape the future of workplace technology.

Exposure to cutting-edge AI, automation, and data engineering initiatives.

High-impact role within a fast-growing technology company scaling globally.

Collaborative culture focused on ownership, innovation, transparency, and continuous learning.

Opportunities for professional growth while working on complex technical challenges.

Ability to influence technical strategy and build foundational systems with long-term impact.

Inclusive workplace that values diverse perspectives and encourages everyone to contribute.

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