Data Engineering Team Lead

About us:

At SegmentStream, we are building a cutting-edge marketing technology that is changing how leading businesses analyze and optimize the performance of their online marketing campaigns. 

Our SaaS platform helps advanced digital marketing teams apply our own sophisticated machine learning algorithms to reveal the true incremental value of each marketing channel and campaign, and automatically apply these AI-insights to close the loop of data-driven marketing.

We’ve proven that our technology works and delivers the best ROAS possible for our enterprise clients across the globe. Check our latest success stories and you’ll understand why our solution is the next big thing in the digital marketing world. 

We are fortunate to be VC-backed by one of the world’s leading startup accelerators - TechStars, as well as some biggest names in the B2B SaaS world, including the founders of Pipedrive, Dynamic Yield, and other great companies. We are also proud to say that SegmentStraem is already trusted by over 50 enterprise customers around the world, including the UK, US, Canada, Australia, and lots of European countries. 

Responsibilities:

• Build, lead and manage the team of senior Data Engineers to develop the entire data transformations architecture, ML algorithms, data mining processes, and delivering scalable data solutions within our core SegmentStream product.
• Improve the Data Transformations module to increase the performance and user experience while minimizing the computing cost and the amount any technical issues;
• Constantly innovate on our overall data architecture and ML algorithms to trust the data and insights that our customers (leading brands with 6-8 figure monthly ad spend) will analyze and make really important marketing decisions;
• Pro-actively find issues with current data architecture and prepare elegant technical solutions to mitigate these risks in the future;
• Gather feedback and feature requests from the users of our Data Transformations module — both external (clients) and internal (our Marketing BI team) to understand how to improve the product further;
• Act on the feedback by working closely with our Product team to prioritize and define a product roadmap and engineering backlog;

Requirements:

• People management & team leadership skills — you have experience hiring and leading a high-performing data engineering/data science team.
• A degree in Computer Science, Math, Statistics or similar;
• 3+ years of relevant experience (Data Transformations, ETL/ELT, Data Modeling in the cloud);
• Strong SQL knowledge (you would rate your SQL skills >8/10);
• Experience working with Google BigQuery;
• Experience with Machine Learning (Google BigQuery ML is a bonus);
• Knowledge of Digital Marketing and Web Analytics domain area will be a bonus;
• High standards — you prefer an elegant and scalable technical solution to some dirty ad-hoc hacks;
• Product mindset — you care about the product you build, and how it will be used by other people;
• Great communication skills and positive personality to work in a team;
• A desire to join a fast-growing global tech startup and make a real impact on its success;
• Ability to speak and write in English with confidence (B2 or higher);

Why SegmentStream:

• Unique and high-quality SaaS product that solves a massive problem for a huge market;
• A vast portfolio of enterprise customers around the globe including the UK, US, Canada, Australia, and lots of European countries;  
• VC-backed by top investors & angels, including TechStars, founders of Pipedrive, Dynamic Yield, and other great SaaS entrepreneurs;
• Fast-growing, fully distributed, and international team of smart people who not only love what they do but are also really good at it;
• A great company culture that is embracing functional ownership, entrepreneurial mindset, and personal growth;
• Full responsibility from day one and being part of our results-driven working environment;
• A lot of opportunities for future career growth within the company;
• Fully remote environment;