Python Developer/ Consultant

Overview

On Site
Depends on Experience
Full Time

Skills

API
Amazon RDS
Amazon SageMaker
Amazon Web Services
Artificial Intelligence
Automated Testing
Continuous Delivery
Continuous Improvement
Continuous Integration
Data Architecture
Data Engineering
Data Warehouse

Job Details

Job Title: Python Developer/ Consultant
Location: NYC, NY
Duration: Full Time
Job Description:
full-stack data engineering skills to join our innovative, dynamic team. This role focuses on building reliable, scalable data products and user experiences that power AI/ML modeling, agentic workflows, and reporting. You will work end-to-end - from data ingestion and transformation through to UI - to deliver production-grade solutions in a collaborative, fast-paced environment.
Our application stack runs entirely on AWS and includes Angular for the frontend; Python/Django with AWS managed PostgreSQL (RDS/Aurora) for the API layer; Elasticsearch for search; SageMaker for machine learning; and Python/Celery for background processing. We also leverage Terraform for infrastructure as code, GitHub Actions for CI/CD, and Kubernetes (EKS) for container orchestration. We are investing heavily in our data architecture, leveraging Snowflake, data transformation tooling (e.g. dbt), and modern data ingestion frameworks.
Key Responsibilities:
  • Collaborative development: - partner with business stakeholders, data scientists, and engineering teammates to define and adopt modern data engineering practices.
  • Full-stack data engineering: - build across the entire stack, including data ingestion/acquisition and transformation, APIs, front-end components, and automated test suites.
  • Specification and design: - translate short- and long-term business requirements, architectural considerations, and competing timelines into clear, actionable specifications.
  • Code quality: - write clean, maintainable, efficient code that adheres to evolving standards and quality processes, including unit tests and isolated integration tests in containerized environments.
  • Continuous improvement: - contribute to agile practices and provide input on technical strategy, architectural decisions, and process improvements.
Required Skills & Experience:
  • Professional experience: 5+ years in software engineering, with a full-stack background building data-intensive applications using Python, Kubernetes, relational and non-relational databases, and modern UI technologies.
  • Backend expertise: 3+ years working with Python and Django; building scalable, containerized services with robust APIs and comprehensive unit/integration tests.
  • Modern data engineering: Strong experience with relational SQL databases (e.g. PostgreSQL), data warehouses (e.g. Snowflake), Data Transformation tooling (e.g. dbt), and NoSQL databases.
  • Testing and QA: Solid understanding of unit testing, CI/CD automation, and quality assurance processes to ensure reliable, maintainable code.
  • Agile methodology: Working knowledge of Agile development practices and workflows.
  • Education: Bachelor s or Master s degree in Computer Science, Statistics, Informatics, Information Systems, or a related quantitative field.
Preferred Skills & Experience:
  • Machine learning and AI: Hands-on experience with large language models (LLMs) and agentic frameworks/workflows.
  • Search and analytics: Familiarity with the ELK stack (Elasticsearch, Logstash, Kibana) for search and analytics solutions.
  • Cloud expertise: Experience with AWS cloud services; familiarity with SageMaker; and CI/CD tooling such as GitHub Actions or Jenkins.
  • Front-end expertise: Experience building user interfaces with Angular or a modern UI stack.
  • Financial domain knowledge: Broad understanding of equities, fixed income, derivatives, futures, FX, and other financial instruments.
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.