Data Engineer I

Dataiku is looking for a Data Engineer I to join our Enterprise Data and Analytics (EDA) team. As a member of the EDA team, you will play a central role in delivering data to fuel analytics and data-driven insights to various stakeholders and teams within the company. You will also be a key technical member contributing to the data platform that fuels centralized analytics, embedded analytics teams, Generative AI engineering, and self-service users across the organization.

This role is about 50% Data Operations, Support & Troubleshooting, and 50% new development. The data engineering day-to-day will primarily be within the data platform built using Snowflake, Dataiku, and GitHub. Primary development will focus on Python & SQL, DataOps processes built within GitHub Actions & Dataiku, and data platform processes built within Snowflake & Dataiku.

Non-technical skills and learning are also critical, as you will collaborate with engineers from various teams and help deliver solutions across a wide variety of technical domains. The ideal candidate is naturally curious, has excellent verbal and written communication skills, a sharp analytical mind, a positive attitude towards work, and thrives when collaborating towards a shared goal.

This is an internal and non-client facing role.

 

What you’ll do: 

Dataiku is unique in that every Dataiker is encouraged to use our own product within our Enterprise Data Platform.  That means this is a unique opportunity to deliver a scalable platform with governed data to fuel an entire company of current or potential Data Analysts & Data Consumers! Your responsibilities within the team include but are not limited to:

• Develop engineering expertise within the Dataiku Platform to help maintain and develop system integrations, platform automations, and platform configurations.

• Develop engineering expertise  within Snowflake for data engineering and security/governance features

• Build & maintain python & SQL data replication & data pipelines on large & often complex data sets 

• Build & maintain data quality metrics & observability to help drive data quality standards

• Learn about existing systems and  processes across Data Platforms, Data Engineering and Data Governance

• Troubleshoot data pipelines, platform automations, data access system.

• Help field and troubleshoot various community questions and challenges

• Own, maintain and enhance data operation processes, monitoring & data quality systems

• Design data models for both short term and long term use cases to support data warehouse scalability

• Build & maintain administration systems and applications for monitoring, alerting, data observability, access management, platform metrics