Senior Data Engineer

As a Senior Data Engineer reporting to AVP - Product Strategy, you'll play a critical role in strengthening Nasdaq's Global Connectivity Services (GCS) data capabilities — improving data quality, building scalable pipelines, and enabling better commercial and operational decision-making across teams in New York, Stockholm, and Vilnius.

You'll thrive in this role if you're analytical, self-driven, and passionate about turning complex data into actionable insight in a fast-paced, globally connected environment.

• Build, maintain, and improve data pipelines, models, and datasets that support GCS reporting, billing reconciliation, and operational planning.
• Analyze customer behavior, product usage, and service trends to deliver insights that drive commercial opportunities for Sales and Product teams.
• Lead billing and inventory reconciliation across multiple internal and external data sources, including discrepancy reporting and alerting.
• Create trusted, well-governed data foundations that enable advanced analytics, automation, and future AI-driven use cases.
• Collaborate with Product, Sales, Finance, and Data Center Operations to translate business needs into scalable, practical data solutions.

• Bachelor's degree in Computer Science, Business, or a related field, or equivalent practical experience.
• Proven experience in data engineering, analytics engineering, or a similar data-focused role.
• Strong SQL skills with experience building structured data transformations and automated workflows.
• Hands-on experience with modern data and analytics tools such as dbt, QuickSight, Power BI, or similar platforms.
• Experience working with data from multiple systems and reconciling inconsistent or incomplete data sources.
• Clear communicator with the ability to work effectively with both technical and non-technical stakeholders across time zones.

Nice to have

• Experience with AWS-based data platforms and related tooling.
• Background in billing, inventory, compliance, or operational control processes.
• Exposure to AI, automation, or data foundation work supporting future AI use cases.

• We offer a competitive, well-rounded rewards package designed to support the financial, physical, and emotional well-being of our employees and their families (where applicable).
• We utilize a structured job architecture and career framework to ensure growth opportunities are transparent, fair, and accessible to all employees.