Specialist Solutions Architect - Data Engineering (Financial Services)

This role can be remote. 

As a Specialist Solutions Architect (SSA) - Data Engineering on the Financial Services team, you will guide customers in building big data solutions on Databricks that 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 Apache Spark™ and expertise in other data technologies.  SSAs help customers through design and successful implementation of essential workloads while aligning their technical roadmap for expanding the usage of the Databricks Lakehouse 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 an area of specialty - whether that be streaming, performance tuning, industry expertise, or more.

The impact you will have:

• Provide technical leadership to guide strategic customers to successful implementations on big data projects, ranging from architectural design to data engineering to model deployment
• Architect production level data pipelines, including end-to-end pipeline load performance testing and optimization
• Become a technical expert in an area such as data lake technology, big data streaming, or big data ingestion and workflows
• Assist Solution Architects with more advanced aspects of the technical sale including custom proof of concept content, estimating workload sizing, and custom architectures
• 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 customer-facing technical role with expertise in at least one of the following:
  • Software Engineer/Data Engineer: data ingestion, streaming technologies - such as Spark Streaming and Kafka, performance tuning, troubleshooting, and debugging Spark or other big data solutions
  • Data Applications Engineer: Build use cases that use data - such as risk modeling, fraud detection, customer life-time value
• Extensive experience building data pipelines using big data technologies such as Spark/Delta or Hadoop
• Maintain and extend production data systems to evolve with complex needs
• Production programming experience in SQL and Python, Scala, or Java
• Deep Specialty Expertise in at least one of the following areas:
  • Experience scaling big data workloads that are performant and cost-effective
  • Experience with Development Tools for CI/CD, Unit and Integration testing, Automation and Orchestration, REST API, BI tools and SQL Interfaces (e.g. Jenkins)
  • Experience designing data solutions on cloud infrastructure and services, such as AWS, Azure, or GCP using best practices in cloud security and networking
  • Experience implementing industry specific data analytics use cases
• [Desired] Degree in a quantitative discipline (Computer Science, Applied Mathematics, Operations Research)
• Ability to travel up to 30% when needed

Benefits

• Comprehensive health coverage including medical, dental, and vision
• 401(k) Plan
• Equity awards
• Flexible time off
• Paid parental leave
• Family Planning
• Gym reimbursement
• Annual personal development fund
• Work headphones reimbursement
• Employee Assistance Program (EAP)
• Business travel accident insurance
• Mental wellness resources