Staff Software Engineer

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

Fivetran is seeking a Staff Software Engineer to build and work on data pipelines that move data from various sources to data warehouses. The role involves ensuring technical excellence, contributing to code, reviewing code, and mentoring junior colleagues. The engineer will work with Cloud APIs, SQL, and NoSQL databases, processing terabytes of data into clean, incremental, automated updates.

What you'd actually do

  1. You'll be working with Cloud APIs, SQL, and NoSQL databases, events, data warehouses etc.
  2. You'll be working on the core data pipeline that moves terabytes of data from all our customers to their data warehouse.
  3. You will process the data into clean, incremental, automated updates.
  4. As a technical leader in the team, you will drive engineering excellence within the technology team, come up with architecture and design, work closely with engineers in the team to review designs and contribute directly to code.

Skills

Required

  • Strong technical and problem-solving skills, with recent hands-on software development experience
  • Experience in architecting reliable distributed systems, with an emphasis on high-volume data management within enterprise and/or web-scale products and platforms that operate under strict SLAs
  • Experience and expertise in building back-end services and data systems
  • Broad technical knowledge which encompasses Software development and automation
  • Experience with use of wide array of algorithms and data structures
  • Strong knowledge and expertise in working with Java, AWS, Cloud-based APIs, databases, data warehouses, software design and programming best practices
  • Entrepreneurial mindset, excellent communication, and technical leadership skills
  • Mentoring and guiding junior staff
  • Strong knowledge and expertise in writing SQL queries and understanding of query execution plans

Nice to have

  • Experience with Data Warehouses.
  • Expertise with database management system and storage systems.

What the JD emphasized

  • strict SLAs