Senior Engineer-1

Senior Engineer, Investments Technology

You'll be joining the Investments Technology organization supporting the Solutions business unit, where we build and maintain platforms that empower portfolio managers, quantitative researchers, analysts, and client engagement teams.

You will primarily support the ECOS application and the broader model delivery platform, which is responsible for transforming, validating, and delivering investment model content to internal and external destinations. The team is known for its deep technical expertise, strong engineering culture, and commitment to reliability, innovation, and high-quality delivery.

We are seeking a Senior Engineer, Investments Technology, to design, enhance, and support capabilities within the model delivery platform, including ECOS. This role will partner closely with quantitative research teams, model owners, and downstream consumers to ensure accurate, timely, and scalable delivery of model content across multiple channels (e.g., S3, FTP, email, websites, and internal systems).

This individual will work in a fast-paced environment requiring strong data engineering capabilities, attention to detail, and a mindset focused on reliability and automation. The role reports to the Director, Investments Technology supporting the Solutions business unit.

Responsibilities of the role include:

• Designing, building, and maintaining data-engineering workflows that support model delivery across multiple destinations.
• Developing and extending the ECOS platform components responsible for ingesting, transforming, validating, and routing model content.
• Building robust SQL Server/T-SQL–based logic for data processing, validation, auditing, and error handling.
• Implementing scalable Python services, microservices, and automation tools supporting the end-to-end delivery lifecycle.
• Designing and operating CI/CD pipelines for model delivery services.
• Ensuring data quality, completeness, and traceability through proper logging, monitoring, and operational tooling.
• Working closely with quantitative researchers and model owners to improve delivery workflows and enhance platform usability.
• Experimenting with new tools, design patterns, and technologies to continuously improve reliability, performance, and maintainability.
• Participating in on-call rotation or escalation support for production model delivery processes (as needed).

Requirements of the role include:

• Bachelor's degree in Computer Science, Engineering, Data Science, or related field.
• 3+ years of hands-on experience in software engineering or data engineering (financial services or asset management experience preferred).
• 3+ years of SQL Server and T-SQL experience, including complex query design, stored procedures, performance tuning, and ETL workflows.
• 3+ years of Python experience, including data processing, service development, or automation frameworks.
• Strong experience with data engineering concepts (data modeling, data pipelines, validation frameworks, lineage, error handling).
• Hands-on experience with modern CI/CD and Dev Ops practices.
• Experience with AWS services (e.g., Lambda, S3, Step Functions, Fargate, Aurora, Terraform) preferred.
• Experience designing scalable systems and APIs for data-delivery use cases.
• Experience working with structured and unstructured datasets.

Skills / Other Personal Attributes

Required:

• Ability to work with ambiguity—imperfect data, evolving requirements, and conceptual model logic—and convert them into reliable technical solutions.
• Strong analytical, debugging, and problem-solving skills.
• Highly self-motivated and capable of taking ownership with minimal supervision.
• Strong written and verbal communication skills, including documentation.
• Enthusiasm for challenging, thought-provoking engineering work with a desire to learn and grow.
• Ability to manage multiple tasks and priorities effectively.
• Positive, team-oriented attitude and willingness to collaborate.
• Ability to work effectively under pressure and meet tight deadlines.
• Strong interpersonal skills and willingness to listen and incorporate feedback.
• Structured, disciplined approach to engineering with high attention to detail.
• Adaptability—comfort…