Data Engineer II

Dataiku•Miami, OH

12h

About The Position

Dataiku is the Platform for AI Success, the enterprise orchestration layer for building, deploying, and governing AI. In a single environment, teams design and operate analytics, machine learning, and AI agents with the transparency, collaboration, and control enterprises require. Sitting above data platforms, cloud infrastructure, and AI services, Dataiku connects the full enterprise AI stack — empowering organizations to run AI across multi-vendor environments with centralized governance. The world’s leading companies rely on Dataiku to operationalize AI and run it as a true business performance engine delivering measurable value. For more, visit the Dataiku blog, LinkedIn, X, and YouTube. Dataiku is looking for a Data Engineer II 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, AI, 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, Generative AI engineering, embedded analytics teams, and self-service users across the organization. You will become a technical expert on the various platforms we work in and help drive engineering excellence both within the EDA team and across the wider Analytics Community. 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. Strong software development lifecycle knowledge and DataOps skills are a must. 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.

Requirements

3+ years of relevant experience in Data Engineering / Data Platform Engineering
Expertise in SQL & Python is a must. Experience in Dataiku DSS is a big plus.
Prior experience with Snowflake strongly desired
Prior experience with DevOps technologies such as Github Actions, Azure DevOps or Jenkins
Strong understanding of data architecture & data modeling concepts
Prior experience building and maintaining replication & data pipelines in a cloud data warehouse or data lake environment
Excellent analytical and creative problem-solving skills - exhibit confidence to ask questions to bring clarity, share ideas and challenge the norm.
Passion for continuous learning and teaching to help learn & teach new technologies & implementation strategies
Experience working with complex stakeholders; dissecting vague asks and helping to define tangible requirements
Ability to manage multiple projects and time constraints simultaneously in a high trust remote environment
Ability to wear multiple hats depending on the project with the focus on accomplishing end goals while inspiring colleagues to do the same
Excellent written and verbal communication skills (especially with senior level stakeholders) with the ability to speak to both the business value, data products, & technical capabilities of a platform. Ability to create clear and concise documentations with a high degree of precision

Responsibilities

Be an expert level engineer within the Dataiku Platform including Platform Automation, GenAI Capabilities, Plugin Development, maintenance & troubleshooting
Be an expert level engineer within Snowflake for data engineering and security/governance features
Build & maintain python & SQL based platform automation process
Build & maintain data quality metrics & observability to help drive data quality standards
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, and end user transparency
Build & maintain GenAI Platform platform solutions focused on security and governance for engineering delivery
Build & maintain DataOps process for SDLC delivery
Identify opportunities for improvements & optimization for greater scalability & delivery velocity
Collaborate closely with Analytics Engineers to provide data & data models for analytical deliverables
Perform root cause analysis on often complex errors to help ensure data pipeline availability
Help drive technical & architectural decisions on the data platform including decisions on data architecture, data engineering processes, data quality frameworks, data access security & governance frameworks, DataOps processes & data consumption models.
Help test new features in Dataiku and partner tools to both provide feedback internally as well as determine value towards internal analytics & data platform integration
Work closely with key stakeholders across the organization including Infra, embedded analytics teams, Product and Engineering to help foster both technical implementations & requirements gathering
Proactively drive innovation internally with dedicated innovation time & projects that aim to be transformational for either the platform, team or company as a whole.
Actively contribute to the expertise level and competencies of the EDA Team and participate in the creation and support of data development standards and best practices.