Databricks Solution Architect

About the Company TekRek has partnered with a growing AI, data, and automation consulting firm delivering enterprise technology projects across North America and international markets. The business works across cloud, data platforms, AI, automation, and business applications. The Role This is a hands-on Databricks architecture role focused on designing enterprise data and AI platforms while staying close to delivery. You’ll work directly with customers from technical discovery through solution design and prototyping, partnering with commercial and delivery teams to make sure proposed architectures are practical and buildable. What You Will Do Design enterprise Databricks architectures using Lakehouse, Delta Lake, and Unity Catalog patterns across AWS, Azure, and GCP environments. Lead customer discovery sessions, unpacking business requirements, data challenges, and existing architecture before defining the technical approach. Build prototypes, proofs of concept, and reusable reference architectures across data engineering, machine learning, and GenAI use cases. Advise customers on data pipelines, modeling, governance, platform integrations, and the technical risks that need to be addressed before delivery. Work alongside account, delivery, data science, and ML engineering teams to turn complex technical requirements into solutions that resonate with engineers and executive stakeholders. What You Bring 5+ years in customer-facing technical roles such as solution architecture, technical consulting, or sales engineering, including 3+ years working hands-on with Databricks and/or Snowflake. Experience designing, presenting, and delivering production-grade enterprise data architectures in AWS, Azure, and/or GCP. Databricks Professional-level certification, such as Data Engineer Professional or Machine Learning Professional. Strong depth in at least one core data discipline: Spark/Kafka-based data engineering, data warehousing and ETL, or data science and machine learning. Strong Python and SQL skills, paired with the communication skills to lead technical discussions and explain architecture decisions to both engineering and business audiences. Why This Role You’ll stay hands-on with Databricks while owning architecture across complex enterprise data and AI engagements, from early technical discovery through prototypes and delivery direction. The scope spans modern data engineering, ML and GenAI, with the opportunity to build reusable technical assets and deepen the wider team’s Databricks capability.

Design enterprise Databricks architectures and lead customer discovery sessions to define technical approaches for data and AI platforms. Build prototypes and proofs of concept while collaborating with cross-functional teams to ensure practical delivery of solutions.

Requires 5+ years in customer-facing technical roles with at least 3 years of hands-on experience in Databricks or Snowflake. Candidates must hold a Databricks Professional-level certification and possess strong Python and SQL skills.

• Microsoft AzurePreferred
• SQLPreferred
• Machine learningPreferred
• Amazon Web ServicesPreferred
• Google CloudPreferred
• PythonPreferred

Identified from the job description. Confirm important requirements above.

• Databricks
• Solution Architecture
• Lakehouse
• Delta Lake
• Unity Catalog
• AWS
• Azure
• GCP
• Python
• SQL
• Spark
• Kafka
• Machine Learning
• GenAI
• Data Engineering
• Technical Consulting

• Data & Analytics
• Consulting
• Technology
• Engineering
• Software

Minimum education

Professional degree

Minimum experience

5+ years

Posting language

English

Working hours

40 hours per week

Seniority

Mid-Senior level

Application method

Direct apply is available