Guide customers in cloud data warehousing transformation with Databricks in a senior technical role.
Posted by employer 1 month ago
First seen on Joblaze 1 month ago
Last verified on the company career page 10 hours ago
Not disclosed in this posting: compensation, work arrangement, visa sponsorship.
Joblaze summary
In the role of Specialist Solutions Architect for Data Warehousing at Databricks, the individual will engage directly with customers to facilitate their transition to cloud-based data warehousing solutions, focusing on architecture design and production deployment. Key skills include expertise in data warehousing technologies, proficiency in SQL and Python, and experience with cloud platforms like AWS, Azure, or GCP. This position is suited for professionals with over five years of technical experience, particularly those with a background in data analytics and customer-facing roles. The role also emphasizes continuous learning and community engagement within the data warehousing specialty.
Quick facts
- How much experience is required?
- At least 5 years of relevant experience for this Specialist Solutions Architect - Data Warehousing role.
- What's the tech stack?
- Joblaze extracted these technologies from the posting: AWS, Azure, GCP, Java, OLAP, OLTP.
- What seniority level is this role?
- Databricks targets senior candidates for this position.
- Is this full-time or contract?
- Full-time for this Specialist Solutions Architect - Data Warehousing role at Databricks.
From the original posting
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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, query conversion, debugging MPP data warehouses or other big data solutions, or migration workloads from EDW or other systems
- Experience with design and implementation of data warehousing technologies including relational databases, SQL, data analytics,, MPP, and OLAP
- Deep Specialty Expertise in at least one of the following areas:
- Experience scaling large analytical data warehouse 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, or Java for developing UDFs
- Experience with the AWS, Azure, or GCP clouds
- 2 years professional experience with data warehousing and big data technologies (Ex: SQL, Redshift, SAP, Synapse, Snowflake, 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
- Bachelor's degree in Computer Science, Information Systems, Engineering, or equivalent work experience
- Native proficiency in Korean is a must, and business-level English is preferred
- Nice to have: Databricks Certification
Standard company text repeated across Databricks's postings is omitted here.