Solutions Architect
Designs and presents scalable Databricks data architectures for customers throughout the sales lifecycle. The role requires 5+ years in pre-sales, technical architecture, or consulting, strong data-platform expertise, and customer-facing communication skills.
About the job
Responsibilities
- Partner with customers to design scalable data architectures using Databricks technology and services.
- Drive complex technology discussions and communicate the value of the Databricks platform throughout the sales lifecycle.
- Engage customer technical leads, including architects, engineers, and operations teams, as a trusted advisor.
- Develop account strategies with Sales and other partners to grow customer platform usage.
- Establish the Databricks Lakehouse architecture as customers' standard data architecture through technical account planning.
- Build and present reference architectures and demo applications for prospects.
- Consult on big data architectures, data engineering pipelines, and data science and machine learning projects.
- Prove Databricks technology for strategic customer projects and validate integrations with cloud services and third-party applications.
- Promote Databricks open-source projects, including Spark, Delta Lake, MLflow, and Koalas, through meetups, conferences, and webinars.
- Travel to customers in the region up to 30% of the time.
Requirements
- 5+ years of experience in a customer-facing pre-sales, technical architecture, or consulting role.
- Expertise in at least one of the following areas:
- Big data engineering, such as Spark, Hadoop, or Kafka
- Data warehousing and ETL, such as SQL, OLTP, OLAP, or DSS
- Data science and machine learning, such as pandas, scikit-learn, or HPO
- Data applications, such as log analysis, threat detection, real-time systems monitoring, or risk analysis
- Ability to translate customer business needs into technology solutions and establish buy-in with stakeholders at all levels.
- Experience designing, architecting, and presenting data systems for customers and managing delivery of production solutions.
- Fluency in SQL and database technology.
- Debugging and development experience in Python, Scala, Java, or R.
Nice-to-haves
- Experience building solutions with AWS, Azure, or Google Cloud.
- Degree in a quantitative discipline such as Computer Science, Applied Mathematics, or Operations Research.
Compensation
- Canada pay range: $164,500–$224,000 CAD.
- Total compensation may include an annual performance bonus, equity, and regional benefits.
Skills
Databricks, Spark, Hadoop, Apache Kafka, SQL, ETL, Python, Scala, Java, R, AWS, Microsoft Azure, GCP, Delta Lake, MLflow
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