This role is heavily focused on hands-on data engineering and the practical application of AI/LLMs for automated data extraction, validation and transformation to enterprise grade data model. You will design, build, and maintain high-throughput ETL pipelines, architect robust data models, and deploy intelligent automation frameworks to ingest and parse structured and unstructured financial data at scale.
We’ll trust you to
Design, build, and optimize scalable data pipelines to ingest, transform, and deliver high-volume financial data using Python, SQL, and modern enterprise data technologies, including workflow orchestration, distributed processing, messaging frameworks, and cloud-based data platforms.
Develop robust data architectures and automated ingestion frameworks that support structured and unstructured data sources, enabling scalable, high-performance data processing, schema design, and seamless interoperability across downstream systems.
Leverage AI, Large Language Models (LLMs), NLP, and machine learning to extract, normalize, and enrich Corporate Actions data (e.g., dividends, stock splits, rights offerings) from issuer filings, regulatory disclosures, news, press releases, exchange feeds, and other complex data sources.
Implement intelligent Human-in-the-Loop (HITL) workflows and data quality frameworks that combine AI-driven extraction with automated validation, business rules, statistical methods, and exception management to maximize accuracy, completeness, and operational efficiency.
Develop monitoring, reporting, and observability solutions by creating data quality dashboards, pipeline health metrics, and SLA monitoring capabilities that provide visibility into data integrity, processing performance, and operational effectiveness.
Partner cross-functionally with Product, Engineering, Data Science, and business stakeholders to design scalable data solutions, standardize engineering best practices, and deliver high-quality data products that support trading, analytics, and client-facing applications.
You’ll need to have
Bachelor’s Degree or Master’s Degree in Computer Science, Data Engineering, Information Systems, Quantitative Finance, or an equivalent quantitative discipline.
3+ years of hands-on experience in a Data Engineering or technical Data Management role, with a proven track record of building scalable ETL/ELT pipelines in a production environment.
Advanced technical proficiency in Python (Pandas, PySpark, or standard data manipulation libraries) and complex SQL/NoSQL database engineering.
Hands-on experience applying AI/LLMs and Machine Learning (e.g., LangChain, LlamaIndex, AI Assisted APIs, Hugging Face, or custom NLP models) for structured/unstructured document processing and automated information extraction.
Demonstrated experience with modern data tech stacks, including workflow orchestration engines, message streaming platforms, distributed computing frameworks, and object storage systems.
Strong data modeling and schema design skills, with experience creating structures optimized for analytical capabilities.
Exceptional problem-solving abilities, numerical proficiency, high attention to detail, and strong communication skills to present technical concepts to diverse stakeholders.
We’d love to see
Direct experience ingesting, normalizing, and processing exchange-disseminated US Equity Corporate Actions data (e.g., dividends, stock splits, rights offerings) and equity reference data.
Industry certifications such as Certified Data Management Professional (CDMP) or Data Capability Assessment Model (DCAM).
Experience designing Human-in-the-Loop operational tooling and exception management workflows.
Familiarity with Agile methodologies, backlog management, and modern data governance frameworks.
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.
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