Data Engineer - NYC Based
New York City
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 HavePlaying a pivotal role in optimizing data processing systems and emphasizing design, you’ll be responsible for architecting, developing, and improving our automated data pipelines. You understand the intricacies of data quality and have a keen eye for catching and rectifying quality issues in the underlying data.
This position involves utilizing a robust background in data engineering, a solid grasp of data processing technologies like Spark and PySpark, and a passion for ensuring the integrity and accuracy of the data that drives our solutions.
Our ideal candidate will immediately provide value by:* Designing, developing, and maintaining automated data pipelines using Python, Spark, PySpark, and related technologies* 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:* Bachelor's degree in computer science, software engineering, or a related field* Experience with Spark, PySpark, or other data processing frameworks* Experience with SQL and NoSQL database technologies* 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 is included in our total package for all levels at Qloo.
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: Airflow APIs AWS Computer Science Data pipelines Data quality Engineering NoSQL Pipelines PySpark Python Spark SQL Testing
Perks/benefits: 401(k) matching Career development Competitive pay Equity Health care Parental leave
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