Build the infrastructure and tooling required for optimal extraction, transformation and loading of data from a wide variety of data sources using cloud native big data services from AWS/Azure
Build and maintain the data pipelines that feed our AI systems, including retrieval and knowledge pipelines used by AI agents and RAG applications
Help design and maintain our data and knowledge architecture, including data and knowledge cataloging that makes sources discoverable and usable across AI pipelines
Maintain and operate our Azure infrastructure — provisioning and setting up the right resources, keeping environments healthy, and driving cost optimization and right-sizing
Deploy analytics tools that utilize the data pipeline to provide actionable insights into customer usage, operational efficiency and other analytical and business performance metrics
Work with stakeholders including business analysts and data scientists to assist with data-related technical issues, support their data (infrastructure) needs, and prepare data for modeling and analytics
Support effective, data-driven decision making across stakeholders

Proven experience building and optimizing big data pipelines and architectures on large datasets (tens to hundreds of TB scale)
Working knowledge of stream & batch processing into highly scalable data/metrics stores
Advanced SQL and hands-on experience with relational & non-relational databases like Postgres, Redshift, Cassandra, Data Explorer, etc.
Strong programming skills — Python is a must, Spark a plus
DevOps skills for cloud infrastructure — provisioning resources, infrastructure-as-code, monitoring, and cost optimization (Azure preferred)
Experience with data and knowledge cataloging or data governance tooling is good to have
Experience building big data consumption patterns such as data APIs and visualization platforms is good to have
Degree in Computer Science, Data Science, Data Engineering, or related; a Master's is a plus

A competitive compensation package
Time and resources to grow and develop, including a personal development budget and paid leave for learning days
Paid access to e-learning resources such as O’Reilly and LinkedIn Learning
Enhanced parental leave plus paid leave to care for loved ones and volunteer in local communities
Work flexibility, with two days in the office per week
Improve your home office with a setup budget
Enjoy options to work from your home country and abroad for a set number of days each year
Take the holidays you want with a competitive holiday plan plus an extra day off to celebrate your birthday
Join annual events like our Hackathon and DevDays to bring your ideas to life with talented teammates
Inclusive global culture with collaboration across more than 80 nationalities

Senior Data Engineer

Key skills