Senior Software Engineer

About the Role

We’re looking for a Senior Software Engineer to build and evolve core capabilities for Fivetran’s Datalakes platform. In this role, you will work on systems that enable reliable, scalable, and high-performance movement of data into datalake ecosystems, while helping ensure correctness, operability, and long-term maintainability.

The work is diverse and hands-on, ranging from building new platform capabilities and improving existing services to solving reliability, scale, and performance challenges in distributed systems. You will be responsible for driving technical excellence for your team and owned services by contributing code, reviewing designs and implementations, shaping architectural decisions, and mentoring junior engineers.

As a Senior Software Engineer on the Datalakes team, you will help build and strengthen the platform foundations needed to support datalake and catalog-oriented workflows. The ideal candidate is technically strong, pragmatic, collaborative, and motivated by solving complex engineering problems at scale.

This is a full-time position based out of our Bangalore office. Our hybrid work model offers a blend of remote flexibility and in-person collaboration, including two days in the office each week to connect and build as a team.

Technologies You’ll Use

• Java, SQL
• Kubernetes, Docker
• AWS, GCP
• Buildkite, CircleCI
• Datalakes and Catalog technologies

What You’ll Do

• Build and evolve backend services and platform capabilities for Fivetran’s Datalakes ecosystem.
• Design, develop, and maintain reliable distributed systems that move and process large volumes of data at scale.
• Work on core data pipeline capabilities that enable clean, incremental, and automated data movement for customers.
• Build foundational services and engineering patterns for the Datalakes team, with a strong focus on scalability, correctness, reliability, and operability.
• Review requirements, technical designs, and implementation plans to provide meaningful engineering feedback.
• Improve system performance, resilience, and debuggability across services and workflows.
• Contribute to architectural design and make thoughtful technical decisions that balance speed, quality, and maintainability.
• Collaborate closely with cross-functional teams to deliver robust and customer-facing platform capabilities.
• Use modern engineering tools, including basic AI-assisted tooling where appropriate, to improve development productivity and debugging workflows.

Skills We’re Looking For

• Strong technical and problem-solving skills, with recent hands-on software development experience.
• Experience building reliable distributed systems, with an emphasis on high-volume data processing within enterprise and/or web-scale products operating under strict SLAs.
• 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.
  
  AI & Productivity Engineering
  
  
• 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.
  
  Datalakes
  
  
• Exposure to datalake technologies and concepts such as object storage, file-based table formats, metadata management, and large-scale data processing workflows.
• Familiarity with concepts related to catalogs, schema evolution, partitioning, and data consistency is a plus.
• Understanding of common datalake reliability challenges such as duplicate processing, late-arriving data, schema drift, and incremental data handling is desirable.
• Experience or exposure to building or supporting integrations with datalake and catalog ecosystems is a strong plus.

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