Description & RequirementsAs a Data Engineer within Data AI, you will build and evolve the infrastructure, data pipelines, and operational tooling that power scalable AI and data workflows. You will enable reliable data collection, annotation, training, and evaluation processes by developing systems that improve data quality, operational visibility, and workflow efficiency. Through automation, observability, and platform engineering, you will help create the foundations that allow teams to deliver data and AI products with confidence and at scale.
We'll trust you to: - Design, build, and maintain scalable data pipelines that support data collection, annotation, training, evaluation, analytics, and reporting workflows.
- Develop and operate systems for dataset management, storage, versioning, and lifecycle governance to ensure reliable and reproducible AI workflows.
- Implement monitoring, observability, and alerting capabilities that provide visibility into data quality, system health, and operational performance.
- Build dashboards, tooling, and self-service capabilities that improve transparency, efficiency, and decision-making across data operations.
- Partner with Product, Engineering, and Data teams to evolve the infrastructure and platforms supporting AI-enabled products and workflows.
- Identify bottlenecks and opportunities for automation, delivering scalable solutions that improve reliability, consistency, and operational efficiency.
You'll need to have: - Bachelor's degree in Finance, Business, Economics, Accounting, STEM or degree-equivalent qualifications
- 3+ years in data engineering (Python, SQL)
- Experience building ETL/data pipelines at scale and creating data collection frameworks for structured and unstructured data
- Experience with data modeling and developing proactive data quality strategies that ensure data is fit for purpose
- Experience working with ML/AI datasets or experimentation workflows.
- Excellent problem-solving and analytical thinking skills with strong attention to detail.
- Proven track record of stakeholder relationship management, communication, and cross-team collaboration.
We'd love to see: - Keen interest in and familiarity with generative AI frameworks and the requirements of Agentic AI.
- Experience in semantic structures or large scale data modeling
- Experience using data visualization tools such as Tableau, QlikSense, or PowerBI
- Experience developing or managing annotation programs and training/evaluation datasets for ML or NLP models.
- Deep domain expertise in financial markets/news and understanding of our customers' needs.
If this sounds like you: Apply! If you think we're a good match. We'll get in touch to let you know the next steps!
Salary Range = 110,000 - 190,000 USD Annual + Benefits + Bonus
The referenced salary range is based on the Company's good faith belief at the time of posting. Actual compensation may vary based on factors such as geographic location, work experience, market conditions, education/training and skill level.
We offer one of the most comprehensive and generous benefits plans available and offer a range of total rewards that may include merit increases, incentive compensation (exempt roles only), paid holidays, paid time off, medical, dental, vision, short and long term disability benefits, 401(k) +match, life insurance, and various wellness programs, among others. The Company does not provide benefits directly to contingent workers/contractors and interns.
