Senior Software Engineer - Data Engineering

Location Type

Remote

Role

Data

Level

Senior

Language (main)

Java

About Zendesk

Zendesk started the customer experience revolution in 2007 by enabling any business around the world to take their customer service online. Today, Zendesk is the champion of great service everywhere for everyone, and powers billions of conversations, connecting more than 100,000 brands with hundreds of millions of customers over telephony, chat, email, messaging, social channels, communities, review sites and help centers. Zendesk products are built with love to be loved. The company was conceived in Copenhagen, Denmark, built and grown in California, taken public in New York City, and today employs more than 4,000 people across the world.

The intelligent heart of customer experience

Zendesk software was built to bring a sense of calm to the chaotic world of customer service.

Zendesk believes in offering our people a fulfilling and inclusive experience. Our hybrid way of working, enables us to purposefully come together in person, at one of our many Zendesk offices around the world, to connect, collaborate and learn whilst also giving our people the flexibility to work remotely for part of the week.

About the Job

We’re looking for a smart, adaptable Senior Software Engineer to help build and evolve our real-time data ingestion platform. You’ll work at the intersection of software engineering and data infrastructure, designing and maintaining scalable systems that stream high-quality, trusted data from Kafka to Snowflake via Snowpipe Streaming.

This role emphasizes data quality, observability, and pipeline reliability, and involves developing robust monitoring and alerting systems. You’ll join a high-performing team, contribute to architecture decisions, and collaborate with other engineers while shaping how data flows across Zendesk’s ecosystem.

Key Responsibilities:

Design, build, and maintain data quality systems and pipelines.
Work with tools such as Snowflake, Docker/Kubernetes, and Kafka to enable scalable, observable data movement.
Collaborate cross-functionally to close skill gaps in DQ and data platform tooling.
Contribute to building internal tooling that supports schema validation, data experimentation, and automated checks.
Collaborate cross-functionally with data producers, analytics engineers, platform teams, and business stakeholders.
Own the reliability, scalability, and performance of ingestion systems deployed on AWS
Architect and build core components of our real-time ingestion platform using Kafka, Snowpipe Streaming.
Champion software engineering excellence — including testing, observability, CI/CD, and automation
Drive the development of platform tools that ensure data quality, observability, and lineage through Protobuf-based schema management..
Participate in the implementation of ingestion best practices and reusable frameworks across data and software engineering teams.

Core Skills:

Solid programming experience (preferably in Java)
Experience with distributed data systems (Kafka, Snowflake)
Familiarity with Data Quality tooling and concepts
Good working knowledge of SQL (especially for diagnostics and DQ workflows)
Experience with containerization (Docker, Kubernetes)
Strong debugging, observability, and pipeline reliability practices

What You Bring:

A systems mindset with strong software engineering fundamentals.
Passion for building resilient, high-throughput, real-time platforms.
Ability to influence technical direction across teams and drive alignment.
Strong communication and mentoring skills.
A bias toward automation, continuous improvement, and platform thinking.

Nice to Haves:

Experience with GenAI tools or supporting ML/AI data workflows
Familiarity with cloud-native data platforms (e.g., AWS, GCP)
Exposure to dbt or ELT frameworks

Why Join Us?

You’ll work with experienced engineers who value collaboration, pragmatism, and adaptability. We’re aiming to build resilient systems and a great team culture—not just implement buzzwords.