Data Engineer -- NYC

The Company You’ll Join

At Qloo, our cutting-edge Taste AI technology leverages extraordinary amounts of data—over half a billion records of public figures, places, and things, plus a globe-spanning consumer behavior and sentiment database—to unearth deep insights about consumer preferences. From understanding global travel trends to curating the perfect restaurant recommendation based on your unique tastes, our Taste AI engine sifts through the noise to find the signals that matter. 

And the best part? Qloo's API suite is powered by cultural entities, not personal identities, ensuring our insights are derived without relying on personally identifiable information. Read more about our recent Series C funding here.

The Team You’ll Work With

Reporting to the Director of Data Engineering, you’ll work cross-functionally across the Engineering organization to emphasize designing and optimizing data processing systems for maximum performance, efficiency, and accuracy. Our team is composed of top-notch engineers and scientists who are passionate about creating data-driven solutions that make a lasting impact. We are a growing team dedicated to advancing Taste AI.

Hear what the team has to say  –  “The team culture at Qloo is highly collaborative and supportive, with a strong emphasis on mutual assistance. Each team member is approachable and committed to lending a hand, creating an environment where everyone feels supported and valued...” - Sreekant, VP of API Engineering.

The Impact You’ll Have

You’ll be playing a pivotal role in creating robust data pipelines that power Taste AI and make the results accessible through our API. You will be responsible for understanding the intricacies of the data sources to architect, develop, and improve our automated data pipelines.

Our ideal candidate will immediately provide value by:

+ Designing, developing, and maintaining automated data pipelines on Airflow using Python, PySpark, and SQL (Presto/Trino) 

+ Ensuring data quality by being proactive in catching and rectifying quality issues in underlying data

+ Collaborating with data scientists and other engineers to define data requirements and structures

+ Writing unit tests and conducting system testing to ensure the reliability and integrity of data

+ Optimizing data pipelines for maximum speed, scalability, and accuracy

+ Staying up to date with emerging trends and technologies in data engineering, data processing, distributed computing, and data quality assurance

To be a successful match, you must have:

* 2 - 5 years of experience in data engineering

* Bachelor's degree in computer science, software engineering, or a related field

* Experience with SQL. Experience with Spark would be preferred,but not a requirement

* Experience with automating data processing through Python libraries like Airflow

* Strong problem-solving and analytical skills with keen attention to detail

* Experience with AWS or other cloud platforms

* Ability to manage multiple projects simultaneously and meet tight deadlines

What We Offer

* Competitive salary and equity package, and holistic perks and benefits, including:

- 100% health insurance coverage, with ability to join group dental and vision for a nominal fee

- Team lunches every Thursday in NYC office

- 4% 401K matching

- 20 paid time off days

- 5 paid sick days

- 12 weeks of paid parental leave

- 10+ annual company holidays 

* Opportunities for professional development and growth within a dynamic environment

* A supportive and inclusive company ethos where your ideas are valued, your contributions are recognized, and your impact is tangible

* The chance to be part of a small but mighty team that's making waves in the industry and shaping the future of technology

* Beautiful HQ in Soho, NYC with the opportunity to work in-office, if desired

We are open to different backgrounds and tenure for this hire and compensation will be commensurate with experience. Please note that equity may also be included in our total package, depending on role and level.