Data Architect

You Are:
The Chip and Joanna Gaines at developing data pipelines. Like turning a fixer-upper house into the best on the block, you turn complicated datasets into useful, show stopping formats. You live in the cloud and open-source world and enjoy working with your team to bring all the pieces of the data story together, keeping ratings high and viewers wowed. What does a good time look like to you Hanging out on the reddit big data feeds and chatting about the latest advances in machine learning and AI. And of course, you always stay tuned for what's coming next.

The work:

• Use your expertise to drive data and AI architecture and technology decisions

• Provide insights that influence the overall strategy and plan for a scalable data solution or product that meets business needs

• Educate customers on how to craft highly scalable, flexible, resilient, secure, and cost-effective architectures

• Link technology with measurable business value and outcome

• Identify and investigate new tools and technologies 

• Translate client needs into digestible requirements

Here's what you need:

• Experience communicating with technical and non-technical audiences

• Experience with cloud-hosted data service design (e.g., AWS, Azure, GCP)

• Hands-on experience with ETL processes, data warehousing, and big data technologies

• Proficiency in data modeling, database design, and data governance

• Experience with data integration, data quality, and data security best practices

• Experience with platforms like Databricks, Snowflake, or Palantir

• Must be a U.S. Citizen (No Dual Citizenship)

Bonus points if you have: 

• Cloud first solutions experience 

• Experience with creating platforms and automating processes through writing scripts or software 

• Software development, systems engineering, infrastructure, security, networking, data & analytics 

• Proficiency in programming languages such as Python, Java, or Scala, and experience with SQL.

• Experience with creating data platforms and automating data processes through scripting or software development

• Knowledge of software development, systems engineering, infrastructure, security, networking, data & analytics
• Familiarity with machine learning frameworks and tools (e.g., TensorFlow, PyTorch, Scikit-Learn)