Location:  Northeast, US

REQ ID - FEQ327R20

We are looking for pre-sales professionals who have a successful track record helping large enterprises become more data-driven. Working with the Enterprise Account Executive (AE), the Sr. Solutions Engineer defines and directs the technical strategy for our largest and important accounts, leading to more widespread use of our products and wider and deeper adoption of ML & AI. You will lean upon your background in value selling, technical account management and technical leadership to maximize success in these accounts. While you work with a team that includes hands-on resources who will build proofs of concept and demonstrate Databricks' products, you need to be technical and must understand the relevance and application of ML & AI within a range of use cases important to the target accounts in the greater region.

The impact you will have:

• You work with multiple clients as the main technical voice for Databricks.
• You lead your customers on a transformational journey, helping them to evaluate and adopt Databricks as part of their strategy
• You implement the technical strategy in the account, in close understanding of the strategy.
• You build a movement of technical champions within the account.
• You align technical strategies around Databricks solutions.
• You work with your sales team and technical peers to drive business outcomes for our clients

What we look for:

• Proficiency at establishing virtual teams, and leading them to ultimate success within the account.
• Experience working very large (> $1m ARR), global accounts.
• Form relationships with executives and influencers.
• Present a convincing point-of-view to important decision-makers that leads them down a path of success.
• Technical in big data, data science and cloud (Azure & AWS).
• An ability in data-driven business transformation, and driving change with data.
• Production programming experience in Python, R, Scala or Java
• Nice to have: Databricks, Snowflake, AWS or Azure Certification

FEQ227R259

Mission

Solutions Architects at Databricks lead the growth of the Databricks Data Intelligence Platform. As a team, we have expertise in cloud platforms, data engineering, data analytics, and data science, machine learning, and AI. As a member of our team, you will exercise and grow your expertise in those areas, using open source projects such as Apache Spark™, Delta Lake, and MLflow. This is a customer-facing role, where you will work with customers, your teammates, the product team, our post-sales team,s and partners, to identify use cases for Databricks, develop architectures and solutions using our platform, and guide customers through the implementation, to accomplish meaningful outcomes for their businesses. In this process, you will build relationships with our customers, identify and cultivate champions, and establish yourself as a trusted advisor. You will report to a Field Engineering Manager within the Financial Services team at Databricks.

The impact you will have:

• Partner with the sales team to help customers understand how Databricks can help solve their business problems
• Provide technical leadership for customers to evaluate and adopt Databricks
• Consult on big data architecture, execute proof of concepts for strategic customer projects, and validate integrations with cloud services and other 3rd party applications
• Build and present reference architectures, how-tos, and demonstrate applications for customers
• Become an expert in, and promote open source projects (Apache Spark™, Delta Lake, MLflow, and Unity Catalog) across developer communities through meetups, conferences, and webinars
• Travel to meet with customers in your territory

What we look for:

• 8+ years in a customer-facing pre-sales role, or consulting role - preferably working with big-data technologies to solve data engineering and big-data analytical challenges
• Experience designing and architecting distributed data systems
• Comfortable programming in, and debugging, at least one of: Python, SQL, Scala, Java, or R
• Experience working with global system integrators, consulting organizations, or financial services technology, or financial services data providers is a positive differentiator 
• Experience building solutions with public cloud providers such as AWS, Azure, or GCP
• Experience with Data Engineering technologies (Ex: Spark, Hadoop, Kafka)
• Experience with Data Warehousing technologies (Ex: SQL, OLTP/OLAP/DSS)
• Undergraduate degree or higher in an engineering or mathematics discipline such as Computer Science, Applied Mathematics, Electrical Engineering, etc.)

FEQ227R119

As a Specialist Solutions Architect (SSA) - Data Warehousing, you will guide customers in their cloud data warehousing transformation with Databricks which span a large variety of use cases. You will be in a customer-facing role, working with and supporting Solution Architects, that requires hands-on production experience with large-scale data warehousing technologies and lakehouse architecture. SSAs help customers through evaluations and successful production planning for their business intelligence workloads while aligning their technical roadmap for the Databricks Data Intelligence Platform. As a deep go-to-expert reporting to the Specialist Field Engineering Manager, you will continue to strengthen your technical skills through mentorship, learning, and internal training programs and establish yourself in the data warehousing specialty - including performance tuning, data modeling, winning evaluations, architecture design, and production migration planning.

The impact you will have:

• Provide technical leadership to guide strategic customers to successful cloud transformations on large-scale data warehousing workloads - ranging from evaluation to architecture design to production deployment
• Prove the value of the Databricks Intelligence Platform for customer workloads by architecting production workloads, including end-to-end pipeline load performance testing and optimization
• Become a technical expert in an area such as data warehousing evaluations or helping set up successful workload migrations
• Assist Solution Architects with more advanced aspects of the technical sale including custom proof of concept content, estimating workload sizing and performance, and tuning workloads for production
• Provide tutorials and training to improve community adoption (including hackathons and conference presentations)
• Contribute to the Databricks Community

What we look for:

• 5+ years experience in a technical role with expertise in data warehousing - such as query tuning, performance tuning, troubleshooting, data governance, debugging MPP data warehouses or other big data solutions, or migration workloads from EDWother systems
• Experience with design and implementation of data warehousing technologies including relational databases, SQL, data analytics, NoSQL, MPP, OLTP, and OLAP
• Deep Specialty Expertise in at least one of the following areas:
• Experience scaling large analytical data workloads in the cloud that are performant and cost-effective
• Maintained, extended, or migrated a production data warehouse system to evolve with complex needs, including data modeling, data governance needs, and integration with business intelligence tools
• Experience migrating on-premise EDW workloads to the public cloud
• Bachelor's degree in Computer Science, Information Systems, Engineering, or equivalent experience through work experience
• Production programming experience in SQL and Python, Scala, or Java
• Experience with the AWS, Azure, or GCP clouds
• 2 years professional experience with data warehousing and big data technologies (Ex: SQL, Redshift, SAP, Synapse, EMR, OLAP & OLTP workloads)
• 2 years customer-facing experience in a pre-sales or post-sales role
• Can meet expectations for technical training and role-specific outcomes within 6 months of hire
• Can travel up to 30% when needed