Job Description
- Design and build the data arbitration and decision engine to resolve conflicts across multiple data sources, determining which values to publish.
- Drive the standardization and automation of our ingestion pipelines across structured, unstructured, and internal sources.
- Conduct data profiling and analysis to identify quality gaps, inconsistencies, and opportunities for process improvement.
- Implement data lineage, observability, and monitoring frameworks to ensure transparency, traceability, and reliability.
- Collaborate with Engineering and Product to define and evolve platform requirements and technical architecture.
- Apply a data product mindset—balancing engineering efficiency with data quality, client needs, and long-term maintainability.
- Support the integration of AI/LLM-based tools as part of our larger data processing and enrichment strategy.
*Please note we use years of experience as a guide, but we certainly will consider applications from all candidates who are able to demonstrate the skills necessary for the role.
- 4+ years of experience in data engineering, data architecture, or data automation roles.
- Experience working with financial data, especially within reference or entity/company data domains.
- Strong proficiency in a programming language (e.g., Python, Java, Scala) and modern data tooling (e.g., Spark, Airflow, Kafka).
- Strong SQL skills for data transformation, validation, and reconciliation
- Demonstrated experience working with large-scale datasets, ideally in domains such as reference or entity data.
- Experience with multi-source data arbitration, data normalization, and resolving conflicts across heterogeneous datasets.
- Deep understanding of data governance, quality frameworks, and metadata management.
- Strong analytical mindset and experience with data profiling and validation techniques.
- Proven ability to work independently and cross-functionally in a fast-evolving environment.
- Excellent communication skills and the ability to explain technical decisions to stakeholders with varying levels of technical knowledge.
- Experience building decision engines using rules-based logic and/or AI/ML or LLM-based models
We’d Love to See:
- Familiarity with frameworks like DCAM or DAMA-DMBOK.
- Experience working in AWS and/or Azure for cloud-native data processing and storage
- Proficiency with Git and CI/CD pipelines for reliable, production-grade deployments
- Familiarity with cloud data services (e.g., S3, EMR, Glue, ADLS, Data Factory, Databricks)
- Experience implementing data observability tools (e.g., Monte Carlo, OpenLineage, or custom solutions).
Does this sound like you?
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.