Journey Architect, Digital Self Service

Databricks' success depends on building trust and engagement with an ever-growing audience of data scientists, analysts, and data engineers. We're building out our Self-service team to drive awareness and adoption of data engineering, data science, machine learning, and deep learning technologies. These technologies include popular open-source projects (e.g. Delta Lake, MLflow, Koalas) and the Databricks Platform.

We're looking for a technical journey architect with growth and go-to-market experience in data science and/or data engineering. If you have a passion for problem-solving and building digitized customer engagement programs at scale, thrive in strong cross-functional working relationships, and can collaborate effectively, this opportunity will be exciting for you. You’d be our champion in making Databricks simple!

Day in a life: 

• Analytics and Problem-Solving: 
• Inform and build data analyses, and machine learning models to understand user segmentation and target users across the customer lifecycle.
• Thrive in ambiguity, love figuring things out, and are energized by new challenges.  
• Journey orchestration: 
• You’d be responsible for building self-serve experiences that span the customer journey. You will be responsible for conceptualizing, orchestrating, and evolving digital-led user journeys to deliver customer value and move the needle on consumption. You will own the strategy, roadmap, and execution of these experiences both in-product and out-of-product. 
• You’d simplify the adoption of the Databricks platform. At Databricks we work on some of the most complex distributed processing systems and our customers challenge us with interesting new big-data processing requirements. As the complexity grows for us and our customers, we are looking to our journey architects to strategize and lead customers to solutions. This is done oftentimes by teaching the product to new users in scalable settings such as roundtable discussions. 
• Design, own, and manage the revenue, digital engagement, and product impact of user journeys. You will optimize current processes and build blueprints to communicate and collaborate on the design, prototyping, and deployment of these experiences. 
• Databricks expertise
• Learn and become a Databricks + Spark expert! Customers will look to you for advice and expertise via programs such as office hours.
• Cross-functional collaboration
• Collaborate with Sales, Field Engineering, PMM, PM, Enablement, and Engineering to launch an end-to-end digital customer experience that spans both in-product and out-of-product channels.
• Influence the product roadmap with data-driven insights based on customer feedback, support, and operations data.
• Have strong cross-functional skills to communicate and collaborate with the technical support team and other core Databricks teams to ensure that customer requests and escalations are resolved.
• Gather insights and customer feedback in partnership with Sales and CS.

What you’ll build

Get ready to build for scale and dive into the product. If you’re curious, analytical, and can balance a scientific approach with customer empathy, you will love the challenge of building digital-led experiences in this role. You’d embody a CEO mindset, orchestrating and leading the digital customer experience for our customer base. You’d focus on iteratively building up impact and creating efficiencies for the field and Sales teams. You are able to have technical discussions with data scientists and engineers and demonstrate the value of Databricks.

The goal is to help our customers to become successful and enthusiastic Databricks champions. Armed with customer insight, you’d work across enablement, sales, product, engineering, support, and marketing teams to bring the best of learning, community, and thought-leadership content to each user. 

The impact you will have will span across our global customer base:

• Drive awareness and engagement of Data Engineering (Delta Lake), Machine Learning and Deep Learning capabilities (PyTorch, TensorFlow, Spark MLlib, Koalas, etc.), and Machine Learning Lifecycle (e.g. MLflow). You'll position Databricks by establishing yourself as a technical leader and managing the customer journey.
• Partner as part of our cross-functional Growth team and build product requirements for digital experiences based on customer research, data analysis, and financial forecasting.  
• You have a growth mindset and can partner cross-functionally to align goals and success metrics across the organization
• Use your creativity and imagination to build excitement around data engineering, data science, and machine learning technologies. We encourage new approaches and thought-provoking content.
• Partner with PMs, PMMs, and CSE SMEs to personalize user journeys and integrate predictive models in partnership with Data & Eng.
• Collaborate with our content team to curate messages that compel users to complete high-impact actions in the product.
• Strategize and identify new use cases to grow accounts and align them to 1-to-many programs to deliver at scale. Find areas where Databricks can provide the most value to increase renewals. 
• Engage with the product team to guide customer requests and establish our roadmap.
• Grow and increase the user engagement of new users to drive faster time to value and accelerate revenue growth at scale.
• Identify and achieve targets on product engagement, customer satisfaction, expansions, and new opportunities.
• Develop Databricks champions and produce customer references for the marketing team.
• Be a true proponent of customer advocacy.
• You will inspire, mentor, and coach other team members.

What we look for:

• Minimum 6 years of experience working in customer-facing technical roles (in Customer Success, consulting, or related discipline)
• Experience at a SaaS company or with cloud architectures
• Languages: Python, or SQL
• Familiarity with the end-to-end data analytics workflow
• Experience with databases and data warehousing
• Problem-solving skills, those that apply to a 'big data’ environment
• Some travel may be involved depending on the customer's needs.
• Bachelor's degree in computer science or related field.

Nice to have:

• Fluency with cloud services such as AWS or Azure
• Fluency with distributed streaming platforms (Kafka, Kinesis)
• Experience working with large-scale data processing services (Hadoop)
• Background in machine learning or working with ML tools and services.