Lead Engineer - R01572451

Brillio 2
Bangalore +1 more
On-site

Who this role is best for

Best suited to experienced Python engineers with a focus on building production-grade APIs and data models, working in financial-services or regulated domains.

Best fit for

  • Experienced Python engineers with a track record of building production APIs and data models
    — “5–6+ years of recent, hands-on Python development, including ownership of production services”
  • Candidates with a background in financial services or regulated domains
    — “Financial-services or regulated-domain experience is preferred”

Things to consider

  • The role may require working in a high-performance environment with complex data processing needs
    — “Experience processing large JSON, YAML and SQL datasets, with practical knowledge of batching, retries, idempotency, caching and performance optimisation”
  • Candidates must be familiar with comprehensive software engineering practices beyond just coding
    — “Strong production engineering practices: PyTest, Git, code reviews, CI/CD, deployment, monitoring and production support”

How to stand out

  • Highlight experience with FastAPI and Pydantic in API design and validation
    — “Practical FastAPI and Pydantic experience covering API creation, schema design, complex validation”
  • Showcase contributions to production services and reusable libraries in your resume
    — “5–6+ years of recent, hands-on Python development, including ownership of production services, reusable libraries and automation”
  • Demonstrate your ability to work independently and deliver quickly in interviews
    — “A hands-on go-getter who can contribute from day one, work independently and deliver production-ready solutions quickly”
  • Include examples of data modeling, schema versioning, and lineage in your portfolio or resume
    — “Strong conceptual, logical, physical and metadata modelling, including canonical models, data contracts, source-to-target mapping, schema versioning, lineage and data quality”
Pace · Fast PacedCollaboration · MediumAutonomy · HighDecision Impact · Team

Derived from job-description analysis by Serendipath's career intelligence engine.

What success looks like

  • ownership of production services
  • delivery of production-ready solutions
Typical background
5–6+ years of recent, hands-on Python developmentstrong production engineering practices

Skills & requirements

Required

Python DevelopmentFastapi And Pydantic ExperienceProduction Engineering PracticesData ModelingBatching, Retries, Idempotency, Caching And Performance Optimization

Preferred

Financial-services Or Regulated-domain Experience

Stack & domain

PythonFastapiPydanticGitCI/CDPytestLeadershipCommunicationFinancial ServicesRegulated Domain

About the role

Original posting from Brillio 2 via Lever

Lead Engineer

Job requirements:

5–6+ years of recent, hands-on Python development, including ownership of production services, reusable libraries and automation—not only scripts, notebooks or data analysis. Practical FastAPI and Pydantic experience covering API creation, schema design, complex validation, serialization, async processing, error handling and testing. Strong conceptual, logical, physical and metadata modelling, including canonical models, data contracts, source-to-target mapping, schema versioning, lineage and data quality. Experience processing large JSON, YAML and SQL datasets, with practical knowledge of batching, retries, idempotency, caching and performance optimisation. Strong production engineering practices: PyTest, Git, code reviews, CI/CD, deployment, monitoring and production support. A hands-on go-getter who can contribute from day one, work independently and deliver production-ready solutions quickly. Financial-services or regulated-domain experience is preferred 5–6+ years of recent, hands-on Python development, including ownership of production services, reusable libraries and automation—not only scripts, notebooks or data analysis. Practical FastAPI and Pydantic experience covering API creation, schema design, complex validation, serialization, async processing, error handling and testing. Strong conceptual, logical, physical and metadata modelling, including canonical models, data contracts, source-to-target mapping, schema versioning, lineage and data quality. Experience processing large JSON, YAML and SQL datasets, with practical knowledge of batching, retries, idempotency, caching and performance optimisation. Strong production engineering practices: PyTest, Git, code reviews, CI/CD, deployment, monitoring and production support. A hands-on go-getter who can contribute from day one, work independently and deliver production-ready solutions quickly. Financial-services or regulated-domain experience is preferred

Source: Brillio 2 careers (Lever)

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