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Solutions Architect - Media

Job in Los Angeles, Los Angeles County, California, 90079, USA
Listing for: Cacheflow
Full Time position
Listed on 2026-08-30
Job specializations:
  • IT/Tech
    Data Engineering
Salary/Wage Range or Industry Benchmark: 152000 - 209000 USD Yearly USD 152000.00 209000.00 YEAR
Job Description & How to Apply Below

FEQ
427R216
At Databricks, our core principles are at the heart of everything we do; creating a culture of proactiveness and a customer‑centric mindset guides us to create a unified platform that makes data science and analytics accessible to everyone. We aim to inspire our customers to make informed decisions that push their business forward. We provide a user‑friendly and intuitive platform that makes it easy to turn insights into action and fosters a culture of creativity, experimentation, and continuous improvement.

You will be an essential part of this mission, using your technical expertise to demonstrate how our Data Intelligence Platform can help customers solve their complex data challenges.

You'll work with a collaborative, customer‑focused team that values innovation and creativity, using your skills to create customized solutions to help our customers achieve their goals and guide their businesses forward. Join us in our quest to change how people work with data and make a better world!
As a Sr. Solutions Engineer, you will independently lead technical engagements for customers, owning discovery, solution design, and platform demonstrations. You are a builder who can code, architect, and present—combining technical depth with customer‑facing skills to drive Databricks adoption. You will own frontline customer relationships and work with your Account Executive to develop technical strategies that expand platform usage.

The Impact You Will Have
  • Independently lead technical discovery and solution design for customer workloads spanning data engineering, analytics, and machine learning
  • Build and deliver compelling proofs‑of‑concept and live demos on the Databricks Platform that drive technical wins
  • Own frontline technical relationships with customer engineers, data teams, and technical leads
  • Develop account‑level technical strategies in partnership with your Account Executive to grow platform consumption
  • Navigate competitive landscapes by articulating Databricks differentiation through hands‑on demonstrations
  • Contribute reusable technical assets (notebooks, solution accelerators, reference architectures) to the broader SA community
What We Look For
  • 4+ years in data engineering, solutions architecture, technical pre‑sales, or a hands‑on consulting role
  • Proficient in Python and SQL with demonstrated ability to debug, optimize, and write production‑quality code — live coding is a required interview stage
  • Hands‑on experience designing and implementing data solutions on at least one public cloud platform (AWS, Azure, or GCP)
  • Working knowledge of distributed data systems:
    Apache Spark™, Delta Lake, or equivalent (Hadoop, Kafka, Flink)
  • Experience leading technical customer conversations — discovery, whiteboarding, architecture reviews
  • Familiarity with one or more: data engineering (ETL/ELT, medallion architecture, streaming), data science/ML (model training, MLOps), or SQL analytics
  • Strong presentation and demo skills — you will build and present a live solution during the interview
  • Bachelor's or Master's degree in Computer Science, Engineering, or a quantitative discipline (or equivalent experience)
Nice to Have:
  • Databricks certification or experience with the Databricks Platform
  • Experience with Unity Catalog, Lakeflow Spark Declarative Pipelines, or MLflow
  • Background at a data/AI company, cloud provider, or technical consulting firm
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 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 anticipates utilizing the full width of the range. The total compensation package for this…

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