Automation Test Engineer – Data &

- Platform Engineering

Location: Madrid or Barcelona, Spain

Hybrid: 2–3 days per week from the Madrid/Barcelona office

Contract: Long-term

AI Ways of Working: Mandatory

About the Role

We're looking for an experienced Automation Test Engineer to own Quality Engineering across data and platform engineering.

This is not a Test Lead or Test Management role . You'll be hands-on, building scalable automation frameworks, designing data validation strategies, challenging weak implementations, and creating quality gates that prevent issues from reaching production.

You should be highly comfortable with Python, SQL, data testing, automation frameworks, streaming systems and cloud technologies , while actively using AI-assisted ways of working to accelerate automation and engineering productivity.

What You'll Be Doing

Design and evolve scalable, modular, metadata-driven test automation frameworks

Build automation for batch and streaming data pipelines, APIs and backend services

Develop reusable data testing capabilities for:

SQL assertions and reconciliation

Schema validation and evolution

Data contracts

Lineage and freshness

YAML/JSON-based test configurations

Proactively test failure scenarios including:

Schema drift

Duplicate, missing and out-of-order events

Late-arriving data

Retries, DLQs and backpressure

High-volume and concurrency issues

Validate ETL/ELT pipelines using row, aggregate and hash-based reconciliation

Test incremental loads, backfills and event-processing semantics

Integrate and extend Great Expectations, Soda or similar data-quality tools

Embed automated quality gates into CI/CD and DataOps pipelines

Work with GitHub Actions, Jenkins or equivalent

Develop strategies for synthetic, masked and deterministic test data

Perform performance,



stress and reliability testing across data platforms

Automate security and compliance validations around PII/PHI, encryption, access control and data retention

Work closely with Data Engineers, Platform Engineers and Architects to embed quality early

Analyse production failures and drive root-cause fixes

Reduce flaky tests, false positives and unnecessary compute

Use AI tools and AI-assisted engineering practices wherever possible to accelerate automation

️ Mandatory Skills

Programming &

- Automation

Strong Python

Experience building automation/test frameworks, libraries and CLI tools

Advanced SQL

Strong test automation and framework engineering experience

Data Engineering

DBT

Airflow

Snowflake or similar data platforms

Strong ETL/ELT and data modelling knowledge

Data Quality

Great Expectations, Soda or similar

Data validation and reconciliation

Schema validation and data contracts

Data lineage and freshness

Streaming

Kafka, Kinesis or similar

Event processing and delivery semantics

Experience testing distributed/streaming systems

CI/CD &

- DevOps

Strong Git

Jenkins, GitHub Actions or equivalent

CI/CD quality gates

Cloud &

- Infrastructure

AWS – data and compute services

Terraform, CloudFormation or similar IaC

AI Ways of Working

Practical experience using AI/GenAI tools to improve software testing, automation or engineering productivity – Mandatory

Nice to Have

API contract testing / PACT

UI automation

Data Mesh / Data Product architectures

Prometheus / Grafana

Experience in regulated industries such as Healthcare, Life Sciences or Finance

Security and compliance testing

Experience

9+ years in Automation / Quality Engineering

5+ years building testing frameworks for data platforms at scale

Strong hands-on engineering background rather than test management

Proven experience improving reliability and reducing production incidents

📌 Automation Test Engineer (Madrid)
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