Senior Data Platform Solutions Architect

Databricks; Greater London; On-site; GBP 90,000 - 130,000; Full time

Job summary

Databricks is seeking a Solutions Architect in London to engage with our largest customers across the region and advise on adopting the Data Intelligence Platform. You will collaborate with a cross-functional team of Solutions Architects, Account Executives, and technology specialists to design customized solutions that align with customer goals.

You will work with data engineering/DWH backgrounds, have hands-on Python/SQL experience, and be comfortable with Spark and public cloud platforms

Qualifications

• Experience engaging with complex customers through the sales lifecycle in a technical pre-sales capacity.
• Strong background in Data Engineering or Data Warehousing; ML/AI background a plus.
• Ability to influence decision-makers and orchestrate cross-functional teams.
• Willingness to travel up to 60% to London offices and customer sites.

Responsibilities

• Engage with Databricks' largest customers to advise on adopting the Data Intelligence Platform.
• Develop and execute customer engagement strategies with Account Executives and Solutions Architects in designated accounts.
• Coach account teams on positioning, adoption strategies and execution to achieve outcomes in a defined timeline.
• Lead workshops and develop customer-facing collateral to support the sales cycle.
• Collaborate with cross-functional teams to design and deliver tailored data platform solutions.

Skills

Complex customer engagements

Data Engineering

Data Warehousing

Python

SQL

Spark

Cloud platforms

Databricks Certification

Job description

Databricks is seeking a Solutions Architect in London to engage with our largest customers across the region and advise on adopting the Data Intelligence Platform. You will collaborate with a cross-functional team of Solutions Architects, Account Executives, and technology specialists to design customized solutions that align with customer goals.

You will work with data engineering/DWH backgrounds, have hands-on Python/SQL experience, and be comfortable with Spark and public cloud platforms