Senior Analytics Engineer (Remote from Poland)

Opis oferty

At Oversee, we build practical AI solutions for the $1.6 trillion global travel industry.

For over a decade, we have helped travel agencies and global enterprises cut travel costs and work more efficiently. Our AI-based reshopping products, FareSaver for air and HotelSaver for hotels, track booked trips and automatically rebook them when a better rate becomes available.

AgentSee, our agentic AI platform, works alongside travel agents. It reads traveler requests, handles bookings and changes, and takes on routine servicing tasks, so agents can manage more trips while improving service quality.

We're growing fast, with exponential YoY revenue growth and partnerships with some of the world's largest Fortune 500 companies.

If you are looking for a dynamic, fast-paced, and positive environment - and want to help solve a $17B global problem - Oversee is the place to build, grow, and make an impact.

Why join us?

We’re looking for a Senior Analytics Engineer to help shape how data powers our products.

This isn’t a traditional data engineering or BI role. We’re looking for someone who enjoys working at the intersection of data architecture, analytics, product development, and engineering.

You’ll work closely with Product and R&D teams to design and evolve data models, build reliable pipelines, define meaningful metrics, and turn complex data into insights that improve our products and business decisions.

Depending on the product, your work could involve anything from developing data architecture and monitoring systems for our AI-powered platform to analyzing product performance, building customer-facing dashboards, and identifying opportunities to improve features and business outcomes.

You’ll have the autonomy to make technical decisions, influence product development, and take ownership of projects from planning through deployment.

We’re also embracing AI across our development workflows. We believe tools like Claude, Claude Code, Cursor, and other AI-powered solutions can fundamentally change how we work, and we’re looking for someone who’s excited to explore that potential.

Wymagania

• 5+ years of experience in analytics engineering, data engineering, product analytics, or a closely related field
• Strong SQL skills and hands-on experience with data modeling, ETL/ELT pipelines, and analytical systems
• Experience designing data solutions and making architectural decisions, ideally within a product-driven environment
• Strong understanding of data architecture, data quality, and the principles behind reliable, scalable data systems
• A product-oriented mindset. You care about what happens after something is built, how it performs, and whether it delivers value
• Comfortable taking ownership of ambiguous problems, making decisions independently, and driving projects from idea to implementation
• An active user of AI tools, with genuine curiosity about how AI can improve development, analytics, and everyday workflows
• Comfortable working in a fast-moving environment where products, priorities, and requirements continuously evolve

Zakres obowiązków

• Own and continuously improve data models, architecture, and analytics solutions that support our products as they evolve;
• Design, build, and maintain reliable ETL/ELT pipelines, ensuring data quality, performance, and scalability;
• Help define the metrics and data requirements needed to measure product performance, feature adoption, customer behavior, and business impact;
• Build and maintain dashboards, reports, and visualizations for internal stakeholders and external customers;
• Develop and improve monitoring, alerting, and data quality processes to ensure product health and reliability;
• Make architectural decisions independently, balancing technical quality, business priorities, and speed of delivery;
• Use AI tools such as Claude, Claude Code, Cursor, or similar technologies to improve development workflows, automate repetitive tasks, accelerate analysis, and increase productivity;
• Continuously look for opportunities to improve processes, product performance, and the way our teams use data.