Associate Director, Data Ingestion
WFA Digital Insight
The demand for data engineering specialists has surged 27% in the past year, driven by the need for institutions to optimize their risk management workflows. Derivative Path stands out with its innovative AI-driven solutions and commitment to diversity. As an Associate Director of Data Ingestion, candidates should be prepared to scale data import capabilities, leveraging domain knowledge and AI expertise. With a strong background in data engineering, candidates will be well-positioned to succeed in this role.
Job Description
About the Role
As an Associate Director of Data Ingestion at Derivative Path, you will lead the evolution of the company's data import capabilities, driving the development of intelligent and flexible data ingestion infrastructure. This role is critical in removing friction from how clients bring their data into the platform, enabling scalable solutions that enhance risk management and drive operational performance. You will be part of a team that values diversity and inclusivity, with a commitment to creating a sense of belonging for all employees.The Associate Director of Data Ingestion will report to the Director of Data & Insights, partnering closely with Engineering, Product, and AI Lab to build cutting-edge data ingestion infrastructure. This role requires a deep understanding of financial data formats, sources, and reporting structures, as well as experience in data engineering, financial data operations, or capital markets technology.
Derivative Path's cloud-native derivatives platform, DerivativeEDGE, serves banks, credit unions, investment managers, and corporate treasury teams. As the company scales, the need for a robust data ingestion capability has never been more critical. The successful candidate will be responsible for driving the team's capability to ingest data in any format, leveraging AI to reduce manual intervention, accelerate onboarding, and ensure the reliability of the data that powers clients' risk management workflows.
What You Will Do
- Lead and mentor the Data Ingestion team, fostering a culture of ownership and continuous improvement as the team scales its AI-assisted capabilities
- Define and execute the ingestion strategy, prioritizing AI-driven format detection, transformation, and validation across structured, semi-structured, and unstructured data
- Apply domain knowledge of financial data formats to ensure data fidelity across the full trade lifecycle
- Partner with the AI Lab to deploy models that automate field mapping, schema inference, anomaly detection, and format normalization at scale
- Establish metrics around ingestion reliability, latency, and data quality, with a clear definition of done and a bias toward proactive monitoring
- Drive the team's capability to ingest data in any format, leveraging AI to reduce manual intervention and accelerate onboarding
- Collaborate with cross-functional teams to ensure seamless integration of data ingestion capabilities
- Develop and maintain documentation of data ingestion processes and procedures
- Stay up-to-date with industry trends and emerging technologies in data engineering and AI
What We Are Looking For
- 8+ years of experience in data engineering or data operations, with 3+ years in a leadership role managing ingestion pipelines or financial data integration
- Demonstrated experience with financial data formats and sources, including custodian files, prime brokerage feeds, trade repositories, or capital markets data vendors
- Strong understanding of modern ingestion architecture, including streaming and batch patterns, schema management, and cloud-native pipeline tooling
- Hands-on experience applying AI and ML to data problems, including format recognition, field mapping, or anomaly detection, with a bias toward production deployment
- Excellent communication skills, with the ability to align Engineering, Product, and client-facing teams around priorities and drive outcomes in an Agile delivery environment
- Experience with data quality and data governance, with a focus on ensuring the reliability and accuracy of data
- Strong problem-solving skills, with the ability to analyze complex data issues and develop creative solutions
Nice to Have
- Experience with Excel, with a strong understanding of data analysis and visualization
- Knowledge of cloud-based data platforms, such as AWS or Azure
- Experience with data engineering tools, such as Apache Beam or Apache Spark
- Certification in data engineering or a related field
Benefits and Perks
- Competitive salary and benefits package
- Opportunity to work with a cutting-edge cloud-native derivatives platform
- Collaborative and dynamic work environment with a team of experienced professionals
- Flexible work arrangements, including remote work options
- Professional development opportunities, including training and education programs
- Access to the latest technologies and tools in data engineering and AI
- Recognition and reward for outstanding performance and contributions
How to Stand Out
- Develop a strong understanding of financial data formats and sources, including custodian files and prime brokerage feeds.
- Emphasize your experience with AI and ML in your application, highlighting specific projects or initiatives you've led.
- Be prepared to discuss your approach to data quality and governance, including strategies for ensuring data accuracy and reliability.
- Showcase your ability to communicate complex technical concepts to non-technical stakeholders, including client-facing teams.
- Highlight your experience with cloud-based data platforms and data engineering tools, such as Apache Beam or Apache Spark.
- Prepare to discuss your experience with Agile delivery environments and your ability to drive outcomes in a fast-paced and dynamic setting.
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