Staff Engineer - Databricks

About the role

For over 20 years, Smartsheet has empowered teams to manage work seamlessly and scale solutions smarter. Now, in our most ambitious chapter yet, we are uniting human teams with AI agents. By orchestrating the work agents do best, automating manual tasks and uncovering insights at scale, we create the space for people to focus on what truly matters: judgment, creativity, and big thinking. That is magic at work, and it’s what we show up for every day.

You Will:

- Data Architecture and Design: Designing and overseeing the architecture of scalable and reliable data platforms, including data pipelines, storage solutions, and processing systems

- Data Modelling and Management:Developing and implementing data models, ensuring data quality, and establishing data governance policies

- Data Pipeline Development: Building and optimising data pipelines for ingesting, processing, and transforming large datasets from various sources

- Performance Optimisation: Identifying and resolving performance bottlenecks in data pipelines and systems, ensuring efficient data retrieval and processing

- Technology Evaluation and Innovation: Staying abreast of emerging data technologies and exploring opportunities for innovation to improve the organisation’s data infrastructure

- Troubleshooting and Problem Solving: Diagnosing and resolving complex data-related issues, ensuring the stability and reliability of the data platform

- Data Security and Compliance: Implementing data security measures, ensuring compliance with data governance policies, and protecting sensitive data

- Perform other duties as assigned

You Have:

- Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.

- 10+ years of experience in data engineering or a similar role.

- Enterprise SaaS software solutions with high availability and scalability

- Solution handling large scale structured and unstructured data from varied data sources

- Experience in building and maintaining data platform systems such as distributed compute, data orchestration, distributed storage, streaming infrastructure ensuring scalability, reliability, efficiency and security

- Working with Product engineering team to influence designs with data, AI and analytics use cases in mind

- In depth experience in System design involving large Petabytes of data with Databricks Lakehouse

- Experience in modern AI/Data infrastructure patterns, Semantics layer Organizing data for AI agents (metadata, context)

- AWS, GCP, Snowflake and Data pipeline frameworks like Airbyte/Airflow

- Programming languages like Python, SQL, and potentially Java or Scala

- Modern software engineering practices like Kubernetes, CI/CD, IAC tools (Preferably Terraform), Observability, monitoring and alerting

- Solution Cost Optimisations and design to cost