Databricks

Specialist Solutions Architect - Data Engineering

Amsterdam, Netherlands

Live, first seen by us 28 days ago

Pay: Pay not listed
Work setting: Not stated
Employment: Not stated

What you’ll work on

Full posting

Lead technical design, proofs of concept, and workload sizing for strategic customers
Build and optimize scalable batch and streaming pipelines on Databricks
Build operational data layers and run end-to-end performance load testing
Build interactive data applications with Databricks Apps
Mentor peers and deliver technical workshops and community presentations

From the employer’s posting

Lead end-to-end technical design, proof of concepts (PoCs), and workload sizing for strategic customer engagements

Design, build, and optimize scalable, high-performance batch and streaming pipelines

operational data layers (Lakebase), and end-to-end performance load testing on Databricks

Build and operationalize custom user-facing data applications using Databricks Apps

Mentor peers, contribute reusable architecture assets, and deliver technical workshops and community presentations

About Databricks

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.

In the employer’s words · Read in context

Apply at Databricks

Posting record

Report an error

Status in our records: Live
First seen by us: Oct 16, 202628 days ago
Recorded sightings: 127
Last seen by us: Nov 13, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

How this job compares

Time since we first saw it

Day 28

Similar jobs usually come down between day 6 and day 56.

At Databricks, jobs usually come down by about day 63.

From 13,630 similar postings that came down, and 19 of Databricks’s. Coming down is not always a hire.

Databricks is hiring

29 open jobs

Open jobs by the week we first saw them, last 12 weeks.

Data Engineer hiring has slowed
Its jobs tend to stay up a long time
3% of open jobs were reposted

Hiring record

See how this role fits your experience

Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.

Java
Python
Scala
SQL
AWS
Azure
Databricks
Delta Lake
GCP
Hadoop
Kafka
Spark
PostgreSQL

Where the posting names them

- AI-First Builder Mindset: Demonstrated daily reliance on AI coding tools and LLMs to accelerate pipeline development, troubleshooting, and asset generation. - Production Programming & Foundations: Strong production coding skills in Python, SQL, and Scala or Java, with a solid grasp of data modeling and system design fundamentals. - Customer Advisory & Delivery: 5+ years in pre-sales or post-sales technical consulting, managing customer engagements and navigating multi-stakeholder technical discussions.

Nice to haves: - Cloud & Migration Mastery: Hands-on experience with major cloud platforms (AWS, Azure, GCP) and legacy data lake modernisation (e.g., Hadoop migration and cost optimisation). - Application Experience: Background in constructing specialised data applications (e.g., risk modelling, fraud detection, customer lifetime value) across industries as a data expert.

The Role As a Specialist Solutions Architect (SSA) – Data Engineering, you are a hands-on technical authority who guides strategic customers in designing, building, and optimizing production-grade data workloads on the Databricks Data Intelligence Platform. Partnering closely with Account Teams and Solution Architects, you translate complex big data challenges into high-performance, scalable architectures using Apache Spark™ and modern streaming frameworks. In this role, you will drive successful implementations, align technical roadmaps to accelerate platform adoption, and establish deep domain specialization; whether in real-time streaming, performance optimization, or operational data layers, while expanding your impact across Field Engineering.

- Drive Technical Wins & Scope: Lead end-to-end technical design, proof of concepts (PoCs), and workload sizing for strategic customer engagements, acting as a trusted advisor to front-line technical stakeholders to secure technical wins. - Architect Production Data Systems: Design, build, and optimize scalable, high-performance batch and streaming pipelines, operational data layers (Lakebase), and end-to-end performance load testing on Databricks. - Deploy Interactive Data Applications: Build and operationalize custom user-facing data applications using Databricks Apps, transforming data pipelines and AI models into interactive tools.

- Architect Production Data Systems: Design, build, and optimize scalable, high-performance batch and streaming pipelines, operational data layers (Lakebase), and end-to-end performance load testing on Databricks. - Deploy Interactive Data Applications: Build and operationalize custom user-facing data applications using Databricks Apps, transforming data pipelines and AI models into interactive tools. - AI-Native Engineering: Leverage AI coding assistants, LLMs, and agentic workflows (e.g., Genie Code, Cursor) as a force multiplier to rapidly prototype, debug, and deliver architectural assets with full ownership of outputs.

#LI-hybrid 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.

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. Benefits

Benefits 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

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

What we look for: - Deep Data Engineering Expertise: 5+ years in data or software engineering with hands-on proficiency in distributed processing (Apache Spark™, Delta Lake, SDP) and real-time streaming technologies (Spark Streaming, Kafka, CDC). - AI-First Builder Mindset: Demonstrated daily reliance on AI coding tools and LLMs to accelerate pipeline development, troubleshooting, and asset generation.

- Customer Advisory & Delivery: 5+ years in pre-sales or post-sales technical consulting, managing customer engagements and navigating multi-stakeholder technical discussions. - Operational & HTAP Architectures: Practical experience with operational/transactional data layers (Postgres/OLTP), low-latency serving, reverse ETL, and hybrid transactional/analytical processing. Nice to haves:

Upload resume Add LinkedIn

Your next step

Complete your application on databricks.com. The employer’s form will show what is required.

Applying through Greenhouse

No account needed: the form is one page, with an “Autofill my application” option that reads your resume.
Greenhouse doesn’t read resumes over 2.5 MB, or details placed in a header, footer, text box, table or second column. The file still attaches, but a recruiter has to type you in by hand.

Already applied? Track this application

Demand for Data Engineer roles

New Data Engineer postings at the employers we follow are up 7% over the last 6 weeks compared with the 6 before.

August 17Last week

Each bar is one week of new postings. The darkest bars are the last 6 weeks.

Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.

About the role

We file this job under Data Engineer, by the work the posting describes.

Data engineers build and run the pipelines that copy data out of apps and outside services into a warehouse or lake, and fix them when a source changes or a load fails.

Expect SQL, Python, a cloud platform, a scheduler such as Airflow, and often tools for large data such as Spark or Kafka.

An analytics engineer works one step later, turning the raw data a data engineer lands into clean tables people can query.

US government figures for database architects

Median yearly pay, May 2025: $139,500
Expected change, 2025 to 2035: 9.4% more jobsagainst 3.5% for all jobs

The government has no code for data engineers, so these figures are for the closest group, database architects, which includes data integration and data warehousing specialists.

Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1243.

Job description

View original posting ↗

(FEQ128R2)

The Role

As a Specialist Solutions Architect (SSA) – Data Engineering, you are a hands-on technical authority who guides strategic customers in designing, building, and optimizing production-grade data workloads on the Databricks Data Intelligence Platform. Partnering closely with Account Teams and Solution Architects, you translate complex big data challenges into high-performance, scalable architectures using Apache Spark™ and modern streaming frameworks.

In this role, you will drive successful implementations, align technical roadmaps to accelerate platform adoption, and establish deep domain specialization; whether in real-time streaming, performance optimization, or operational data layers, while expanding your impact across Field Engineering.

The impact you will have:

Drive Technical Wins & Scope: Lead end-to-end technical design, proof of concepts (PoCs), and workload sizing for strategic customer engagements, acting as a trusted advisor to front-line technical stakeholders to secure technical wins.
Architect Production Data Systems: Design, build, and optimize scalable, high-performance batch and streaming pipelines, operational data layers (Lakebase), and end-to-end performance load testing on Databricks.
Deploy Interactive Data Applications: Build and operationalize custom user-facing data applications using Databricks Apps, transforming data pipelines and AI models into interactive tools.
AI-Native Engineering: Leverage AI coding assistants, LLMs, and agentic workflows (e.g., Genie Code, Cursor) as a force multiplier to rapidly prototype, debug, and deliver architectural assets with full ownership of outputs.
Enablement & Domain Leadership: Mentor peers, contribute reusable architecture assets, and deliver technical workshops and community presentations to scale expertise across accounts and field teams.

What we look for:

Deep Data Engineering Expertise: 5+ years in data or software engineering with hands-on proficiency in distributed processing (Apache Spark™, Delta Lake, SDP) and real-time streaming technologies (Spark Streaming, Kafka, CDC).
AI-First Builder Mindset: Demonstrated daily reliance on AI coding tools and LLMs to accelerate pipeline development, troubleshooting, and asset generation.
Production Programming & Foundations: Strong production coding skills in Python, SQL, and Scala or Java, with a solid grasp of data modeling and system design fundamentals.
Customer Advisory & Delivery: 5+ years in pre-sales or post-sales technical consulting, managing customer engagements and navigating multi-stakeholder technical discussions.
Operational & HTAP Architectures: Practical experience with operational/transactional data layers (Postgres/OLTP), low-latency serving, reverse ETL, and hybrid transactional/analytical processing.

Nice to haves:

Cloud & Migration Mastery: Hands-on experience with major cloud platforms (AWS, Azure, GCP) and legacy data lake modernisation (e.g., Hadoop migration and cost optimisation).
Application Experience: Background in constructing specialised data applications (e.g., risk modelling, fraud detection, customer lifetime value) across industries as a data expert.
Ecosystem & Culture Contribution: Active track record of technical community engagement, public speaking, open-source contributions, or peer mentoring and interviewing.
Flexibility & Travel: Ability to travel up to 30% for strategic customer engagements and internal alignment.

Notes on the role:

This will be an office-based contract (Amsterdam), with a hybrid schedule, requiring up to 30% travel when needed for customer visits, events & trainings.
An initial 12-month fixed-term contract is to be offered, with the expectation of extending/converting to FTE upon successful completion of the probation period.

#LI-hybrid

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.

Benefits

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.

Source details