Senior Databricks Architect - Big Data Solutions Leader

Hiflylabs; Amsterdam; On-site; EUR 120,000 - 160,000; Full time

Job summary

Hiflylabs in Amsterdam is seeking a Senior Solutions Architect to shape big data strategies for Fortune 500 clients. You will drive architecture, design, and implementation of data pipelines with a focus on Spark and Databricks, in a customer-facing role.

Collaborate with engineering and data teams across AWS/Azure/GCP, deliver training, and orchestrate scalable workloads while ensuring customer success across time zones.

Qualifications

• Hands-on and technical expertise with Apache Spark.
• Databricks Certified Data Engineer Professional certification.
• Over 5 years of experience as Software Engineer or Data Engineer.
• Proficiency in Python, Scala, or Java.
• Experience with cloud platforms (AWS, Azure, or GCP).
• Familiarity with CI/CD, testing, automation, REST APIs, BI tools, and SQL interfaces (e.g., Jenkins).
• Excellent communication skills for presentations to leadership.
• Experience in customer-facing roles such as pre-/post-sales or consulting.
• Interest in ML Engineering, including model lifecycle and MLFlow.

Responsibilities

• Provide post-sales technical leadership to guide customers in designing big data projects.
• Identify initiatives to turn data into actionable business value.
• Architect production workloads and optimize end-to-end pipelines.
• Deliver tutorials and training sessions to promote community adoption.

Skills

Apache Spark

Databricks

Python

Scala/Java

CI/CD

REST API

BI tools

SQL

Communication

Customer-facing

ML Engineering

Tools

Hadoop

NoSQL

MPP

OLTP

OLAP

Jenkins

REST API

Job description

Hiflylabs in Amsterdam is seeking a Senior Solutions Architect to shape big data strategies for Fortune 500 clients. You will drive architecture, design, and implementation of data pipelines with a focus on Spark and Databricks, in a customer-facing role.

Collaborate with engineering and data teams across AWS/Azure/GCP, deliver training, and orchestrate scalable workloads while ensuring customer success across time zones.