Senior Software Engineer, Data Solutions

The Role

In this role, you will own the end-to-end design, implementation, and support of data pipelines (batch and streaming) that feed research models and production analytics. Working closely with quantitative researchers, you’ll translate their models into Python or Java, operationalize machine-learning workflows, and modernize legacy ETL processes. In this role, you’ll leverage AWS, big-data frameworks (e.g., Spark, Flink), and CI/CD best practices to ensure reliable, low-latency data feeds and scalable ML deployments. 

How You'll Help Take Us There

• Data Pipeline Development (Batch & Streaming): 
• • Build scalable ingestion pipelines in Python, Java, and SQL.
  • Use Apache Spark or Flink (or equivalent) to process high-volume data streams with sub-second SLAs.
  • Refactor legacy ETL (often provided as R scripts) into maintainable Python/Java code. 
• Model Translation & Operationalization: 
• • Read, interpret, and reimplement R-based statistical or quantitative models (e.g., regressions, risk metrics) into production-grade Python (NumPy/Pandas/SciPy) or Java.
  • Collaborate with quants to validate outputs, write automated tests, and package models for deployment (containerization or serverless). 
• Cloud & Big Data Infrastructure: 
  • Design and maintain AWS-based data platforms (S3, EMR/Spark, Redshift/Athena/Glue).
  • Optimize data storage (partitioning, bucketing) for performance.
  • Ensure data security, cost efficiency, and best practices (IAM, encryption, monitoring). 
• Streaming & Real-Time Analytics: 
• • Develop real-time feature pipelines consuming market or trade feeds (e.g., Kafka).
  • Apply windowed aggregations, time-series joins, and statistical functions at scale.
  • Integrate static reference data (e.g., bond specs, issuer hierarchies) with streaming jobs. 
• Software Engineering & CI/CD: 
• • Implement automated build/test/deploy pipelines (Jenkins, GitLab CI/CD, or equivalent).
  • Enforce coding standards: modular design, documentation, peer reviews, and automated testing (unit/integration).
  • Instrument pipelines with monitoring and alerting (CloudWatch, Grafana). 
• Cross-Functional Collaboration: 
• • Act as a liaison between Research & Quant, Product, and Infrastructure teams.
  • Present technical designs and progress to stakeholders.
  • Mentor junior engineers on data-engineering best practices and streaming architectures. 

What We’re Looking for  

• Programming & Analytics: 
• • 5+ years in data-engineering or ML-engineering roles.
  • Expert in Python (pandas, NumPy, PySpark) and Java (or JVM-based streaming frameworks).
  • Strong SQL skills: complex queries, window functions, performance tuning.
  • Proven ability to read and translate R code into Python or Java, ensuring parity in statistical outputs. 
• Cloud & Big Data: 
• • Hands-on experience with AWS (S3, EMR/Spark, Redshift/Athena/Glue).
  • Proficiency in designing and maintaining big-data workflows (Spark, Flink, or similar). 
• Streaming Technologies: 
• • Production experience building streaming pipelines (Apache Flink, Spark Structured Streaming, Kafka Streams, or equivalent).
  • Ability to meet low-latency requirements while joining with static datasets. 
• Machine Learning Support: 
• • Exposure to ML lifecycle: feature engineering, model packaging, evaluation, and deployment (e.g., SageMaker or equivalent).
  • Experience operationalizing models as microservices or serverless functions. 
• Domain Knowledge: 
• • Familiarity with Fixed Income markets (bond analytics, yield curves, credit spreads). Equities experience is acceptable if paired with strong quantitative background. 
• Software Engineering Practices: 
• • Solid understanding of CI/CD pipelines and automated testing frameworks.
  • Experience with Git workflows (branching, pull requests, code reviews).
  • Familiarity with containerization (Docker) is a plus. 
• Collaboration & Communication: 
• • Excellent interpersonal skills; able to convey technical concepts to diverse audiences.
  • Demonstrated success in an Agile/Scrum environment. 

Preferred Qualifications 

• B.S or M.S degree in Computer Science, Engineering, Data Science, or a quantitative discipline.
• Experience with infrastructure-as-code (Terraform, CloudFormation) and configuration management.
• Prior work on multi-asset class trading platforms or sell-side institutions.
• Familiarity with ML monitoring and model drift detection tools. 

What You Can Expect from Us

• Hybrid Environment: Our employees enjoy a mix of working in the office and from home
• Free Food: We provide free lunch for employees when they are working in the office. Plus, our offices are stocked with snacks
• Paid Time Off: Competitive PTO package including vacation and personal days, sick leave and charity days
• Generous Parental Leave: Up to 20 weeks fully paid leave
• 401(k): Dollar-for-dollar employer match up to $17,500
• Employee Stock Purchase Plan: Employees can purchase MarketAxess common stock at a discount
• Wellness Stipend: We provide employees with up to $1K annually towards gym memberships, home office equipment and more
• Onsite Healthcare: We offer convenient access to world-class care through Mount Sinai at our Hudson Yards location
• Tuition Assistance and Professional Development: Benefit from live and on-demand learning, role-specific training, employee-led Lunch and Learns and guest speakers
• Core benefits: Highly competitive medical, dental, and vision programs

For job positions in NYC, NY, and other locations where required, the estimated salary range for a new hire into this position is $150,000 USD to $225,000 USD. Actual salary may vary depending on job-related factors, which may include knowledge, skills, experience, and location. You may also be eligible for annual cash incentives, equity, and other benefit programs.

MarketAxess Corporation and its affiliates provide equal employment opportunities to all persons regardless of age, color, national origin, citizenship status, physical or mental disability, race, religion, creed, gender, sex, sexual orientation, gender identity and/or expression, genetic information, marital status, veteran status, or any other legally protected characteristic in the location in which the candidate is applying.

All of your information will be kept confidential according to EEO guidelines.