Data Engineer

Nasdaq Data Link (https://data.nasdaq.com) is transforming how business decisions are made.  

Data is the most important resource of the 21st century, and Data Link is at the heart of the emerging data economy. Over the last decade, we’ve built the world’s largest and most successful data marketplace: a platform where over 400,000 professionals buy, sell, create, and consume data. Data Link today is used by everybody from academics to AIs; from two-person fintech start-ups to billion-dollar hedge funds.  

Technology is at the heart of what we do at Data Link, and our sophisticated data acquisition, discovery, and delivery infrastructure is the foundation of our success. We are currently seeking a Data Engineering Specialist to help us design, build, extend and improve the platform. 

At Nasdaq Data Link, the Data Operations and Engineering (DOPE) division is responsible for the millions of datasets that our users consume every day. 

As part of Data Engineering team in DOPE, you will contribute to building ingestion pipelines that clean, transform, and load alternative, core and internal Nasdaq datasets into Nasdaq Data Link. You will help structure large quantities of unstructured and semi-structured data through a combination of organized analytical thinking, technical data wrangling and precise documentation. You will work to ensure completeness, accuracy, timeliness, and reliability of the data. 

Specifically, you will: 

• Design, implement and support components of our data platform with a strong emphasis on data onboarding and automation 

• Automate data ingestion from various sources  

• Automate data processing, transformation and quality checks 

• Work with various data systems to write distributed data pipelines, and orchestrate real- time & batch processing 

• Participate in and champion the team’s code review process, promoting a collaborative, respectful review culture that prioritizes maintainable data pipelines and best practices 

The ideal candidate will:  

• Have at least 6 years of professional experience in a software/data engineering role 

• Be able to write high-quality, well-documented, high-performance code 

• Be eager to learn new technologies and best practices in data engineering by working with a world-class data team  

• Have a working knowledge of one or more programming languages: Python (required), Java, SQL 

• Have working knowledge of Docker 

• Have working knowledge of Git 

• Have working knowledge of AWS cloud services like S3, EC2, ECS 

• Have working knowledge of using the command line, utilities in Bash/zsh, and interacting with cloud resources without a GUI/web-based interface. 

• Have working knowledge of Databricks. 

• Be entrepreneurial and enthusiastic about working in a fast-paced environment  

• Be able to communicate and write concisely and clearly in English 

• Have a Bachelor of Computer Science/Engineering or equivalent degree, or have equivalent qualifications/experience 

• Databricks Certified Data Engineering Associate or Professional certifications are a plus 

This position offers the opportunity for a hybrid work environment (at least 3 days a week in office, subject to change), providing flexibility and accessibility for qualified candidates