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.
Key Responsibilities- 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.
This position is located in Vilnius and 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.
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).
The base pay for this role is 3500 – 4500 EUR (gross). The actual pay depends on factors like your skills, experience, qualifications, and location. In addition to base pay, we offer short-term incentives (bonus or commission) and long-term incentives (equity), where applicable.
We utilize a structured job architecture and career framework to ensure growth opportunities are transparent, fair, and accessible to all employees. The pay range you see reflects the full salary band for this job level, including room for progression over time.
For more information, visit Nasdaq Benefits & Rewards Career Page.
- 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.
- 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.
