Job VC
DataOps Engineer (Cracow)
Technologies
Description
Who we are: Adaptiq is a technology hub specializing in building, scaling, and supporting R&D teams for high-end, fast-growing product companies in a wide range of industries.
About the Product:
The platform processes 50 TB+ of raw data daily, handles 4M+ requests/second, and reaches over 1 billion unique users weekly. As a DataOps Engineer, you will be the reliability guardian of this data ecosystem - catching issues before they hit production, responding to operational incidents, and building the automation and infrastructure that keeps everything running.
About the role:
We’re looking for a
DataOps Engineer
who will focus on
data reliability, monitoring, and quality
across production pipelines.
This role combines:
proactive work (building monitoring, improving pipelines, adding tests)
reactive work (handling alerts, debugging issues, fixing incidents)
You’ll be responsible for keeping data pipelines stable, accurate, and transparent for downstream teams.
What you’ll do:
Build and maintain monitoring & alerting for data pipelines (freshness, accuracy, health)
Detect anomalies and investigate issues before they affect business
Implement data quality checks, validation rules, and automated tests
Troubleshoot incidents, find root causes, and document solutions
Work with Airflow, Python, and SQL for operational tasks and fixes
Maintain metadata and documentation (tables, lineage, sources)
Improve performance and reliability of existing pipelines
Collaborate with Data Engineers and business stakeholders
Requirements:
3+ years in Data Engineering / DataOps / similar roles
Strong
Python + SQL
Hands-on experience with
Airflow
Experience with
PySpark
Experience with data warehouses (MySQL, Presto, Athena or similar)
Experience with monitoring / observability / alerting tools
Strong focus on data quality and reliability
English for daily communication
Nice to have:
DevOps or NOC background
Experience with data governance / metadata tools
Familiarity with tools like Great Expectations, dbt tests, Monte Carlo
Working setup:
Hybrid format: Kraków office (~10 days/month)
Small, experienced team with high ownership
English-speaking environment
What we offer:
Up to
$5000 salary
20 paid vacation days + public holidays
Fully covered accounting & legal support
Equipment and co-working support if needed
Regular compensation reviews
About the Product:
The platform processes 50 TB+ of raw data daily, handles 4M+ requests/second, and reaches over 1 billion unique users weekly. As a DataOps Engineer, you will be the reliability guardian of this data ecosystem - catching issues before they hit production, responding to operational incidents, and building the automation and infrastructure that keeps everything running.
About the role:
We’re looking for a
DataOps Engineer
who will focus on
data reliability, monitoring, and quality
across production pipelines.
This role combines:
proactive work (building monitoring, improving pipelines, adding tests)
reactive work (handling alerts, debugging issues, fixing incidents)
You’ll be responsible for keeping data pipelines stable, accurate, and transparent for downstream teams.
What you’ll do:
Build and maintain monitoring & alerting for data pipelines (freshness, accuracy, health)
Detect anomalies and investigate issues before they affect business
Implement data quality checks, validation rules, and automated tests
Troubleshoot incidents, find root causes, and document solutions
Work with Airflow, Python, and SQL for operational tasks and fixes
Maintain metadata and documentation (tables, lineage, sources)
Improve performance and reliability of existing pipelines
Collaborate with Data Engineers and business stakeholders
Requirements:
3+ years in Data Engineering / DataOps / similar roles
Strong
Python + SQL
Hands-on experience with
Airflow
Experience with
PySpark
Experience with data warehouses (MySQL, Presto, Athena or similar)
Experience with monitoring / observability / alerting tools
Strong focus on data quality and reliability
English for daily communication
Nice to have:
DevOps or NOC background
Experience with data governance / metadata tools
Familiarity with tools like Great Expectations, dbt tests, Monte Carlo
Working setup:
Hybrid format: Kraków office (~10 days/month)
Small, experienced team with high ownership
English-speaking environment
What we offer:
Up to
$5000 salary
20 paid vacation days + public holidays
Fully covered accounting & legal support
Equipment and co-working support if needed
Regular compensation reviews