DataOps Engineer: Build Reliable Data Pipelines

twentysix; Hilversum; On-site; EUR 112,000 - 130,000; Full time

Benefits offered by this job

Health insurance

PTO & holidays

401k with company contribution

Parental leave

Work-life balance

Career growth

Job summary

Monks is seeking a capable Data Engineer with a strong DataOps focus to join our team. You will embed at Monks, supporting a high-profile client account in Cupertino, CA, building, scaling and maintaining core data pipelines that deliver trusted data to Sales & Finance leadership.

The role requires 5+ years in data engineering or related field, expert SQL, and Python, with hands-on experience in Airflow, Spark, Trino/Dremio, Iceberg, Kafka, and Docker.

Qualifications

• 5+ years of Data Engineering experience (or Software Engineering with a strong data focus).
• Expert-level SQL required.
• Strong Python proficiency.
• Hands-on experience with Airflow, Spark, Trino/Dremio, Apache Iceberg, Kafka and Docker.
• DataOps & Lakehouse architectures familiarity and related tooling.
• Proven track record designing, deploying and maintaining ETL/ELT pipelines and data warehouses.
• Experience with Sales/Finance data domains (preferred).

Responsibilities

• Build and maintain scalable data pipelines from diverse data sources.
• Own workflow orchestration and monitor pipelines using Airflow.
• Contribute to reusable libraries and scalable coding patterns.
• Hardening and reliability improvements across shared pipelines.
• Implement automated data quality checks and observability tooling.
• Manage platform governance and query optimization, including migrations.
• Own incident response and change management for data domains.

Skills

Data Engineering

SQL

Python

Airflow

Spark

Trino/Dremio

Apache Iceberg

Kafka

Docker

Git

CI/CD

DataOps

Lakehouse

Tools

Airflow

Spark

Trino/Dremio

Apache Iceberg

Kafka

Docker

Job description

Monks is seeking a capable Data Engineer with a strong DataOps focus to join our team. You will embed at Monks, supporting a high-profile client account in Cupertino, CA, building, scaling and maintaining core data pipelines that deliver trusted data to Sales & Finance leadership.

The role requires 5+ years in data engineering or related field, expert SQL, and Python, with hands-on experience in Airflow, Spark, Trino/Dremio, Iceberg, Kafka, and Docker.