Senior Data Engineer - Investment Technology
We are seeking a Senior Data Engineer with direct experience in financial services or asset management. This individual will design, enhance, and support capabilities within the model delivery platform, including ECOS, ensuring accurate, timely, and scalable delivery of investment model content across multiple channels (S3, FTP, email, websites, and internal systems).
The role sits within the Solutions business unit and reports to the Director of Investments Technology. You will work in a fast‑paced environment that demands strong data‑engineering skills, exceptional attention to detail, and a mindset centered on automation and operational reliability.
This position is offered on a W‑2 employment basis only; C2C engagements cannot be accommodated.
Responsibilities
- Design, build, and maintain data‑engineering workflows that support model delivery across multiple destinations.
- Enhance ECOS platform components for ingesting, transforming, validating, and routing model content.
- Develop robust SQL Server and T‑SQL logic for processing, validation, auditing, and error handling.
- Build scalable Python services, microservices, and automation tools supporting end‑to‑end delivery workflows.
- Design, implement, and support CI/CD pipelines for model‑delivery services.
- Ensure data quality, completeness, and traceability through strong logging, monitoring, and observability tooling.
- Partner closely with quantitative researchers and model owners to optimize delivery workflows and enhance platform usability.
- Evaluate and adopt new tools, design patterns, and technologies to improve reliability, performance, and maintainability.
- Participate in on‑call or escalation rotations as needed for production delivery processes.
- Bachelor's degree in Computer Science, Engineering, Data Science, or a related field.
- 3+ years of hands‑on software or data‑engineering experience within financial services, asset management, or a closely related domain.
- 3+ years of SQL Server and T‑SQL experience (complex queries, stored procedures, performance tuning, ETL).
- 3+ years of Python experience (data processing, services, automation frameworks).
- Strong foundation in data‑engineering concepts: modeling, pipeline design, validation frameworks, lineage, and error‑handling patterns.
- Hands‑on experience with modern DevOps and CI/CD practices.
- Experience designing scalable systems and APIs for data‑delivery use cases.
- Experience working with structured and unstructured data.
- AWS experience preferred (Lambda, S3, Step Functions, Fargate, Aurora, Terraform).
- Bachelor's in Statistics, Computer Science, or a related technical discipline
- Professional certifications such as CFA, CPA, CIPM, CAIA, or FRM are preferred
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