Databricks

Solutions Architect - Strat Media

Databricks$180K — $247K *
Information Technology
5 - 7 years of experience
Job Overview by Ladders

Qualifications

  • 6+ years in solutions architecture, data engineering, or a technical pre-sales role.
  • Strong coding skills in Python and SQL, capable of live coding and debugging.
  • Expertise in distributed data systems architecture and cloud-native data platforms.
  • Proficient in the Databricks Platform with a growing technical specialization.
  • Proven experience leading architecture discussions with senior stakeholders.
  • Experience with public cloud deployment (AWS, Azure, GCP), focusing on infrastructure and security.
  • Exceptional communication skills for translating technical concepts to business value.

Responsibilities

  • Own the complete technical strategy for customer accounts, from discovery to deployment.
  • Lead architecture discussions to design scalable solutions for data engineering and analytics.
  • Serve as a trusted advisor to senior customer technical teams.
  • Drive wins in competitive scenarios with tailored Databricks solutions.
  • Develop and establish a technical specialization, becoming a key resource within the team.
  • Coordinate across teams to deliver comprehensive solutions to customer needs.
  • Influence product development by providing feedback on customer requirements and gaps.

Benefits

  • Flexible work environment with remote work options.
  • Professional development opportunities, including potential Databricks certifications.
  • Access to industry-leading technology and tools.
  • Collaborative team culture focused on innovation and growth.
  • Opportunity to influence product direction effectively.
Full Job Description
REQ ID FEQ327R527

As a Solutions Architect, you will lead the technical strategy for your customers - owning architecture discussions, driving platform adoption, and serving as a trusted advisor to customer technical leads and architects. You combine deep technical expertise with strategic thinking to position Databricks as the foundation of your customers' data and AI strategy. You are developing a technical specialization (archetype) and are recognized within your team for depth in a specific domain.

The Impact You Will Have
  • Own the end-to-end technical strategy for your accounts, from initial discovery through production deployment and consumption growth
  • Lead complex architecture discussions - designing scalable, production-grade solutions spanning data engineering, ML/AI, and real-time analytics
  • Serve as a trusted technical advisor to customer architects, engineering leads, and Directors
  • Drive technical wins in competitive scenarios by demonstrating Databricks' differentiation through custom-built solutions
  • Develop and declare an emerging technical specialization (archetype) - becoming a go-to resource for your team in that domain
  • Orchestrate cross-functional resources (DSAs, SSAs, Partners) to deliver comprehensive solutions for complex customer needs
  • Influence product direction by providing structured feedback on customer requirements and competitive gaps

What We Look For
  • 6+ years in solutions architecture, data engineering, technical pre-sales, or a senior hands-on technical role
  • Strong coding proficiency in Python and SQL - you must demonstrate live coding, debugging, and solution-building skills
  • Deep expertise in distributed data systems architecture: designing scalable pipelines, streaming architectures, lakehouse patterns, and cloud-native data platforms
  • Proficient on the Databricks Platform (or demonstrated ability to achieve proficiency rapidly) with a developing technical specialization in one area (e.g., real-time/streaming, ML/AI, data governance, migrations)
  • Proven ability to lead architecture discussions with senior technical stakeholders - whiteboarding, design reviews, and trade-off analysis
  • Experience with production deployments on public cloud (AWS, Azure, or GCP), including infrastructure, security, and governance considerations
  • Track record of driving platform adoption and consumption growth within accounts
  • Excellent communication skills - able to translate complex architectures into business value for both technical and executive audiences
  • Ability to travel to customers 30% of the time
  • Bachelor's or Master's degree in Computer Science, Engineering, or a quantitative discipline (or equivalent experience)

Nice to Have:
  • Databricks certifications (Data Engineer, ML, Platform)
  • Experience with competitive platforms (Snowflake, AWS native services, Azure Synapse) - understanding the landscape you'll position against
  • Background in a data/AI company or cloud provider
  • Industry domain expertise (Financial Services, Healthcare, Retail, Media, etc.)

Interview Process: Recruiter Screen → Hiring Manager Screen → Design and Architecture Interview → Live Coding Assessment → Build, Demo, Pitch! Presentation → Reference Check

#CMEG

Pay Range Transparency

Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected base salary range for non-commissionable roles or on-target earnings for commissionable roles. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location. Based on the factors above, Databricks anticipated utilizing the full width of the range. The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above. For more information regarding which range your location is in visit our page here.

Zone 1 Pay Range

$180,000-$247,500 USD

Zone 2 Pay Range

$180,000-$247,500 USD

Zone 3 Pay Range

$180,000-$247,500 USD

Zone 4 Pay Range

$180,000-$247,500 USD

About Databricks

Databricks is a unified analytics platform that provides data engineering, collaborative data science, and machine learning capabilities. The company was founded in 2013 by the original creators of Apache Spark, a popular open-source big data processing engine. Databricks provides a cloud-based platform that allows data teams to collaborate and build data pipelines, run machine learning models, and perform advanced analytics. The company has raised over $1 billion in funding and is valued at $38 billion as of November 2021.
Learn more about Databricks
Size
2,000 employees
Industry
Founded
2013

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