Senior Databricks SSA - $247K+ Data & AI Career Role

Databricks; United States; Remote; USD 180,000 - 248,000; Full time

Job summary

Databricks Inc. is seeking a Data Solutions Architect (SSA) to lead advanced technical strategy for enterprise customers. You will own architecture discussions, design scalable data solutions, and act as a trusted advisor to customer technical leaders and architects.

This role emphasizes real-time analytics, lakehouse patterns, and cloud-native platforms. You will drive platform adoption, orchestrate cross‑functional teams, and contribute to product direction with customer feedback.

Qualifications

• 6+ years in solutions architecture, technical pre‑sales, or senior hands‑on role
• Strong coding in Python and SQL with live coding ability
• Experience migrating EDW workloads across OLAP/OLTP systems
• Hands-on with Spark ecosystem, streaming and data platforms

Responsibilities

• Own end-to-end technical strategy for accounts from discovery through deployment
• Lead architecture discussions across data engineering and real-time analytics
• Serve as trusted technical advisor to customer architects and execs
• Drive technical wins by showcasing Databricks differentiation
• Develop an emerging technical specialization within the team
• Coordinate cross-functional resources to deliver complex solutions

Skills

Spark

Kafka

Lakehouse

Cloud platforms

Python

SQL

Data warehousing

Pre-sales

Communication

Education

Bachelor’s or Master’s in Computer Science

Tools

Snowflake

Redshift

Synapse

Spark

Job description

Compensation & Market Positioning

The $180K–$247.5K base range is above-market for Senior Solutions Architect roles in the US (typical market: $150K–$200K base). Add equity and performance bonuses at a high-growth unicorn like Databricks, and total comp could easily exceed $300K+. This is a genuinely well-compensated role.

Skills You'll Build

This position is a career accelerant for anyone targeting senior data platform or AI infrastructure roles. You'll sharpen:

• Apache Spark, Kafka, and lakehouse architecture at enterprise scale
• Cloud-native data platform design across AWS, Azure, and GCP
• EDW migration expertise (Snowflake, Redshift, Synapse) — one of the hottest skills in 2024–2025
• Executive communication and pre-sales technical strategy

Career Trajectory

SSA roles at Databricks are a recognized path to Principal Architect, Field CTO, or even product roles. The archetype specialization model means you build a recognized niche (e.g., streaming, ML/AI governance) — valuable for personal brand development.

Green Flags

Databricks serves 70% of the Fortune 500, meaning your customer interactions will be high-caliber. The structured interview process (including live coding) signals rigor and a meritocratic culture.

Watch For

The 30% travel requirement and customer-facing pressure can lead to burnout in pre-sales roles. Assess whether the team culture supports sustainable workloads before accepting. Overall, this is a strong opportunity for a senior data engineer ready to move into strategic architecture.

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As a Data Engineering and Warehousing Specialist Solutions Architect (SSA), you will lead the advanced technical strategy for your customers — owning complex 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 further developing a technical specialization and are recognized within the Field Engineering team for depth in the specific domain.

This position can be remote.

The Impact You Will Have

• Own the end-to-end technical strategy for your accounts, from discovery through production deployment and consumption growth
• Lead complex architecture discussions — designing scalable, production‑grade solutions spanning data engineering 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, SAs, 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, technical pre‑sales, or a senior hands‑on technical role in the following areas:
  • Data and Software Engineering: Deep hands‑on experience with Apache Spark™ ecosystem (Spark Core, Spark SQL, Spark Streaming), message queues (e.g., Kafka), batch ingestion, performance tuning, and troubleshooting complex Spark workloads
  • Data Applications Engineering: Experience building or supporting data‑driven use cases, predictive analytics pipelines, or customer analytics platforms
  • Data Warehousing & Migration: Experience migrating EDW workloads (e.g., legacy SQL, Redshift, Snowflake, Synapse, EMR) across OLAP/OLTP systems; advanced query tuning, governance, and MPP debugging
  • [Nice to have] Data Observability & Security: Telemetry, high‑velocity log ingestion, anomaly detection, and familiarity with SIEM tools (e.g., Splunk, Elastic, Sentinel)
• 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
• Bachelor's or Master's degree in Computer Science, Engineering, or a quantitative discipline (or equivalent experience)
• Willingness to travel up to 30% as needed

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

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 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 .

Local Pay Range: $180,000 — $247,500 USD

About Databricks

Databricks is the Data and AI company. More than 20,000 organizations worldwide — including adidas, AT&T, Bayer, Block, Mastercard, Rivian, Unilever, and 70% of the Fortune 500 — rely on the Databricks Data + AI Platform to build and scale data and AI apps, analytics and agents. Headquartered in San Francisco with 30+ offices around the globe, Databricks offers a unified platform that includes Genie, Lakebase, Agent Bricks, Lakeflow, Lakehouse, and Unity Catalog. To learn more, follow Databricks on LinkedIn , X , YouTube , and Instagram .

At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region click here .

Our Commitment to Diversity and Inclusion

At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio‑economic status, veteran status, and other protected characteristics.

Compliance

If access to export‑controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.

Is this Databricks Solutions Architect role truly remote? Yes, the position is listed as remote within the US. However, candidates should note that up to 30% travel is required for customer engagements, so a stable US base is effectively necessary. What is the salary range for this role? The local pay range is $180,000–$247,500 USD annually. Total compensation may also include annual performance bonuses and equity, and varies based on location zone, experience, and certifications. What technical skills are required to be competitive for this role? Strong hands‑on experience with Apache Spark (Core, SQL, Streaming), Python, SQL, and cloud platforms (AWS, Azure, or GCP) are essential. Data warehousing migration experience from platforms like Snowflake, Redshift, or Synapse is also highly valued. What does the interview process look like for this position? The process includes six stages: Recruiter Screen, Hiring Manager Screen, Design and Architecture Interview, Live Coding Assessment, Presentation, and a Reference Check. Expect to demonstrate live coding and architecture design skills. Do I need Databricks certifications to apply? Certifications (Data Engineer, ML, Platform) are listed as nice-to-have, not required. However, proficiency on the Databricks Platform — or the ability to ramp quickly — is expected.

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