Senior AI-First Data Engineer

Smartcat

10h•Remote

About The Position

Data is becoming one of Smartcat’s most strategic assets. As a Senior Data Engineer, you will help build the intelligence layer that powers decision-making, AI agents, automation, and business operations across the company. This is not a traditional data engineering role focused solely on pipelines and dashboards. You will help transform Smartcat’s data platform into an AI-native foundation where business data becomes discoverable, actionable, and consumable by both humans and AI agents. You will partner closely with Data, Product, Engineering, GTM, and AI teams to create a modern data ecosystem that enables self-service analytics, intelligent automation, and agent-driven decision support. We're currently building a modern greenfield cloud data platform and transitioning from legacy on-premise and batch architectures toward cloud-native, streaming-first infrastructure. This is an opportunity to have a significant impact on how Smartcat scales its data capabilities over the next several years. The role aligns directly with Smartcat's transformation into an AI-native company and agentic platform.

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, dbt, Airflow, Python for data engineering, SQL and data modeling, Data warehousing architectures, Data quality frameworks, Data governance practices, Data orchestration and integration
Experience with: Streaming architectures and event-driven systems, Business intelligence platforms, Product analytics platforms, CRM and customer data platforms
AI-First Mindset (Required)
Demonstrate AI-powered development workflows
Demonstrate Automation of repetitive engineering tasks
Demonstrate 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

Nice To Haves

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

Responsibilities

Evolve our architecture into Next Generation Data Platform
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
Turn Business Data into AI-Ready Assets
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
Drive AI-First Data Engineering
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.
Improve Business Intelligence & Data Accessibility
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
Lead Through Technical Excellence
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

Benefits

Remote-friendly work options
Global, connected team
Highly innovative environment using AI across all areas
Opportunity to shape how AI transforms the workplace
Integral role in remaining a leader in AI innovation
Opportunity to reshape the $100B multilingual content industry
Fast, high-quality results at a fraction of the cost
Opportunity to be part of a scaling company (post-Series C, exceeding $100M ARR and $1B valuation)
Commitment to diversity and high performance
Respect and appreciation for unique backgrounds and perspectives
Inclusive environment where team members can be their authentic selves
Steadfast commitment to inclusion
Against discrimination and harassment