Senior Software Engineer

Fivetran Fivetran · Data AI · Bangalore, India · Engineering Department

Senior Software Engineer to build and evolve core capabilities for Fivetran's Datalakes platform, focusing on reliable, scalable, and high-performance data movement into datalake ecosystems. Responsibilities include driving technical excellence, mentoring junior engineers, and contributing to architectural decisions for distributed systems handling large volumes of data.

What you'd actually do

  1. Build and evolve backend services and platform capabilities for Fivetran’s Datalakes ecosystem.
  2. Design, develop, and maintain reliable distributed systems that move and process large volumes of data at scale.
  3. Work on core data pipeline capabilities that enable clean, incremental, and automated data movement for customers.
  4. Build foundational services and engineering patterns for the Datalakes team, with a strong focus on scalability, correctness, reliability, and operability.
  5. Review requirements, technical designs, and implementation plans to provide meaningful engineering feedback.

Skills

Required

  • Strong technical and problem-solving skills
  • recent hands-on software development experience
  • Experience building reliable distributed systems
  • Broad technical knowledge across software development, system design, and automation
  • Strong understanding of algorithms, data structures, and software design fundamentals
  • Expertise in Java, cloud platforms such as AWS or GCP, cloud-based APIs, databases, and programming best practices
  • Experience building, operating, and debugging backend services in production environments
  • Strong ownership mindset, communication skills, and technical leadership abilities
  • Ability to create and contribute to an environment geared toward innovation, high productivity, high quality, and strong customer focus

Nice to have

  • Basic familiarity with AI-assisted developer tools and productivity workflows
  • Ability to use AI tools effectively for tasks such as debugging, documentation, code exploration, or log analysis with appropriate validation of outputs
  • Good judgment in verifying generated results and maintaining quality, reliability, and safety in engineering workflows
  • Interest in using modern tooling to improve engineering productivity and effectiveness
  • Exposure to datalake technologies and concepts
  • Familiarity with concepts related to catalogs, schema evolution, partitioning, and data consistency
  • Understanding of common datalake reliability challenges
  • Experience or exposure to building or supporting integrations with datalake and catalog ecosystems

What the JD emphasized

  • strict SLAs
  • high-volume data processing
  • enterprise and/or web-scale products