Specialist Solutions Architect - Data Warehousing
Guides strategic customers through cloud data warehousing transformations, from technical evaluations and architecture design to production deployment and migration planning. The role requires at least five years of data warehousing experience, production programming skills, cloud expertise, and customer-facing pre-sales or post-sales experience.
About the job
Responsibilities
- Provide technical leadership to guide strategic customers through successful cloud transformations for large-scale data warehousing workloads, from evaluation and architecture design through production deployment.
- Demonstrate the value of the Databricks Data Intelligence Platform by architecting production workloads, including end-to-end pipeline load performance testing and optimization.
- Develop deep technical expertise in areas such as data warehousing evaluations and successful workload migrations.
- Assist Solution Architects with advanced aspects of technical sales, including custom proof-of-concept content, workload sizing and performance estimation, and production workload tuning.
- Provide tutorials and training to improve community adoption, including hackathons and conference presentations.
- Contribute to the Databricks Community.
- Travel up to 30% when needed.
Requirements
- 5+ years of 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 migrating workloads from enterprise data warehouse systems.
- Experience designing and implementing 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:
- Scaling large analytical data workloads in the cloud to be performant and cost-effective.
- Maintaining, extending, or migrating production data warehouse systems, including data modeling, data governance, and business intelligence tool integration.
- Migrating on-premises enterprise data warehouse workloads to the public cloud.
- Bachelor's degree in Computer Science, Information Systems, Engineering, or equivalent experience.
- Production programming experience in SQL and Python, Scala, or Java.
- Experience with AWS, Azure, or Google Cloud.
- 2 years of professional experience with data warehousing and big data technologies, such as SQL, Redshift, SAP, Synapse, EMR, OLAP, and OLTP workloads.
- 2 years of customer-facing experience in a pre-sales or post-sales role.
- Ability to meet technical training and role-specific outcomes within 6 months of hire.
Compensation
- Base salary range: $219,100–$301,300 USD.
- Total compensation may also include an annual performance bonus, equity, and benefits.
Skills
SQL, Python, Scala, Java, AWS, Microsoft Azure, GCP, Databricks, Data Warehousing, Lakehouse Architecture, Data Modeling, Data Governance, NoSQL, Olap, Oltp
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