Senior AI-First Data Engineer

Smartcat is building the future of work with a focus on Agentic AI to enhance productivity for enterprises. The Senior AI-First Data Engineer will transform the company's data platform into an AI-native foundation, enabling self-service analytics and intelligent automation while closely collaborating with various teams to create a modern data ecosystem.

Responsibilities:

• Continue building our data architecture into scalable cloud-native AI-first architecture
• Lead the transition from batch-oriented pipelines to near real-time and streaming data systems
• Improve reliability, observability, governance, and performance across the data stack
• Establish engineering standards and best practices for data development
• Build data products that can be consumed by AI agents, analytics systems, and business users
• Enable semantic layers, metadata management, and knowledge structures that make data more accessible and actionable
• Create foundations for agent-driven reporting, forecasting, and business intelligence
• Help transform business metrics from static dashboards into living operational systems
• Use AI to accelerate development, testing, documentation, monitoring, and operational workflows
• Design systems that allow AI agents to query, understand, and act on business data safely
• Evaluate emerging AI technologies and identify opportunities to increase productivity across the data organization
• Help establish Smartcat as an AI-native data organization, leveraging AI to increase productivity and talent density across the company
• Make analytics simpler and more accessible for non-technical stakeholders
• Improve usability and adoption of BI tools such as Omni and future AI-powered analytics experiences
• Enable self-service analytics without sacrificing governance or data quality
• Reduce time-to-insight across Product, Revenue, Marketing, Customer Success, and Finance teams
• Raise the engineering bar through mentorship, code reviews, architecture leadership, and knowledge sharing
• Influence technical direction across Data Engineering and Analytics Engineering
• Partner with stakeholders to align platform investments with business priorities

Requirements:

• 6+ years of experience in Data Engineering, Analytics Engineering, or a related field
• Proven track record designing and operating modern cloud data platforms
• Experience in high-growth SaaS environments
• Experience working with both technical and business stakeholders
• Demonstrated ability to lead complex projects from design through delivery
• Strong hands-on experience with Databricks
• Strong hands-on experience with dbt
• Strong hands-on experience with Airflow
• Strong hands-on experience with Python for data engineering
• Strong hands-on experience with SQL and data modeling
• Strong hands-on experience with Data warehousing architectures
• Strong hands-on experience with Data quality frameworks
• Strong hands-on experience with Data governance practices
• Strong hands-on experience with Data orchestration and integration
• Experience with Streaming architectures and event-driven systems
• Experience with Business intelligence platforms
• Experience with Product analytics platforms
• Experience with CRM and customer data platforms
• AI-powered development workflows
• Automation of repetitive engineering tasks
• Use of AI for debugging, testing, architecture exploration, and documentation
• Experience integrating AI into data or analytics workflows
• Curiosity about agentic systems and the future of AI-enabled data platforms
• Evidence of measurable productivity gains through AI adoption
• Experience building AI-native data products
• Experience with semantic layers, RAG systems, vector databases, or knowledge graphs
• Experience enabling AI agents to consume operational business data