Direct Client Requirement
Job Title:
Senior Software Engineer (Investments Analytics Technology)
Location:
US-NJ-Jersey City
Type: Full Time/Permanent
Overview
:
The client is seeking a highly skilled and experienced Senior Software Engineer to join our development team and contribute to the ongoing development of our analytics platforms. As a Senior Software Engineer, you will be expected to possess deep technical expertise in our tech stack and stay abreast of the latest industry technology trends. We value team members who are driven to achieve results, maintain high quality standards, and exhibit a flexible entrepreneurial spirit in the face of scope changes. You will be joining a fast-moving team that requires the ability to work autonomously while also collaborating closely with others.
Responsibilities :
Design and develop next-generation equity and credit analytics platforms.
Collaborate closely with business partners and analysts to understand data requirements and analyze and design the necessary data pipeline and database design.
Design, implement and maintain data pipelines that can efficiently and reliably ingest and store data from a variety of internal and external sources.
Develop robust quality control processing, monitoring, and workflow dashboards.
Integrate risk and quantitative models.
Simplify and automate existing manual processes.
Provide support for overnight batch jobs.
Work closely with a team of frontend and backend engineers, product managers, and analysts
What makes this role interesting?
The Investment Analytics Technology team is currently investing significantly in building credit analytics platforms.
The candidate will have significant opportunities to contribute to this project at the ground level.
The candidate will work alongside an established team of developers, quantitative analysts, and portfolio managers to create analytics platforms encompassing quantitative modeling, risk analytics, ESG metrics, and data insights.
The candidate will work closely with professional investment staff and expand their financial knowledge across asset classes, markets, and instruments.
Qualifications :
Bachelor's or Master's degree in Computer Science, Engineering, Physics, Math, or related work experience
Highly experienced candidate with a minimum of 10 years of expertise in application design, coding, testing, maintenance, and debugging.
The ideal candidate excels in building data models from scratch, actively participates in strategic data discussions, proficiently writes complex database objects, and optimizes query performance.
The ideal candidate will have a strong proficiency in Java, Python, REST, Microservices, Spring Boot, API gateway, SQL queries, stored procedures, query optimization performance tuning, and building data models.
3 years of experience working with various cloud technologies, including AWS, Azure, GCP, Snowflake, Spark, and their associated tools.
8 years of experience creating and maintaining Conceptual, Logical, and Physical data models.
Ability to identify opportunities to reuse data and reduce redundancy across the enterprise.
7 years of experience with Git/GitHub.
5 years of experience with DevOps tools like Jira, Confluence, and CI/CD pipelines (Jenkins).
5 years of experience with messaging technologies such as Kafka, as well as queuing technologies and other related tools
.
5 years of experience working in the finance industry (Must have).
Skills
:
Strong analytical skills.
Candidate must be willing to take full ownership of projects, covering discovery, analysis, technical design and implementation, testing, and deployment tasks.
Must demonstrate good communication skills and be comfortable working closely with senior quantitative analysts, risk analysts and business partners.
A strong desire to document and share work done to aid in long term support.
Candidate must be a self-starter, a dependable partner, and team player.
Special Knowledge (nice to have, but not required):
Experience with market data vendors - Bloomberg, Markit, ICE/Client, S&P, Moodys, Fitch, Russell, Intex, JPM, Factset, State Street, CRD, and Yieldbook.
Experience working on distributed system and handling & processing of large-scale data (trades, risk, market data etc).
Experience working in the finance industry.
Knowledge of fixed income analytics for asset types such as corporate bonds, Treasuries, Derivatives, Sovereigns, Bank Loans, MBS, ABS, and CLO.
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