Data Operations Analyst

Why Nasdaq

When you work at Nasdaq, you’re working for more open and transparent markets so that more people can access opportunities. Connections can be made, jobs can be created, and communities can thrive. We want all our employees to have access to opportunity, too. That means planning for career growth, ensuring you have the tools you need, and promoting an inclusive culture where we’re all valued for our unique perspective.

Here, you will work for a global tech leader committed to breaking down barriers to inclusive prosperity. We see technology as a means to free people up to work together more productively and effectively by centralizing data, analytics, and market intelligence.

Here, we’re committed to building a more diverse and inclusive workforce. Not only is it our responsibility to do better, but we also need representative voices to power the fresh thinking that is vital for our business and our clients.

What We Offer

This is a permanent full-time role based in Bonifacio Global City, Taguig following a hybrid work model setup (at least 2 in office days per week).

You can expect an autonomous but fast-paced work environment where you are recognized for your results and ability to drive things forward. Every day brings many opportunities to learn & grow and rewards with a global impact we create.

In return, you will receive HMO coverage for you and your dependents, employee stock purchase plan, equity grant, retirement plan, annual bonus, free counseling sessions, subscription to e-learning platforms, fitness, wellness and more.

What You Will Do

The Data Operations and Engineering (DOPE) division of Nasdaq Data Link is responsible for the datasets that our customers buy and consume every day. We are seeking a Data Operations Analyst to join our growing team.

As part of the Data Operations Team, you will contribute by monitoring and maintaining hundreds of datasets on Nasdaq Data Link. This includes monitoring various tools to ensure dataset timeliness and accuracy, communicating with stakeholders, prioritizing and resolving data issues, and handling various maintenance tasks related to data products. Specifically, you will:

• Continuously monitor a shared email inbox, various Slack channels and PagerDuty to respond to alerts related to data delays.

• Troubleshoot alerts and determine the appropriate course of action.

• Communicate with partners, Customer Success and other stakeholders to keep them aware of ongoing issues.

• Assist the various support teams to resolve outstanding queries from customers and partners.

• Develop your programming skills in Python, Spark and SQL.

• Learn to use new tools such as Databricks and Monte Carlo

What We Expect

• Have 1-3 years of professional experience in understanding data products and data management. Recent graduates are welcome to apply.

• Amenable to work on a rotational shift schedule and accommodate weekend work as the team operates 24/7 depending on business needs.

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

• Able to communicate professionally with internal and external stakeholders.

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

• Have a basic knowledge of Python/SQL/Git and be willing to further develop these skills

• Be eager to learn about parallel processing frameworks, orchestration/scheduling tools, and distributed data systems such as Databricks and Airflow.

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

What Would Be Helpful

• Familiarity with Databricks and Airflow

Does It Sound Like You?

Please follow through by clicking the “Apply” link and submitting your application. If your skills and experience are a match, we will be in touch soon. In the meantime, please visit our website and social media channels to learn more about our innovative business, inclusive culture and discover why Nasdaq Manila is Great Place To Work certified!