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Data Engineer

Migx

Responsibilities

  • architectures, develop cloud-native pipelines, and help implement
  • DataOps practices
  • Build and manage
  • ETL/ELT pipelines
  • using tools like
  • Databricks, dbt, PySpark, and SQL.
  • Contribute to scalable
  • data platforms
  • across
  • cloud environments
  • (Azure, AWS, GCP).
  • Implement and maintain
  • CI/CD workflows
  • using tools such as
  • GitHub Actions
  • and
  • Azure DevOps
  • infrastructure as code
  • for data environments using

Requirements

  • tools.

We’re looking for a

Data Engineer to join our growing Data and AI Engineering team of professionals who thrive at the intersection of data, technology, and healthcare. Whether you're early in your career or already have hands-on experience, we welcome curious minds, team players, and problem-solvers eager to build high-quality data solutions for the life sciences industry.

At MIGx, you’ll contribute to modern data mesh and data fabric that ensure our systems are robust, observable, and production-ready.

Apply

  • DataOps principles: pipeline versioning, testing, lineage, deployment automation, and monitoring.
  • Integrate automated data quality checks, profiling, and validation into pipelines.
  • Ensure strong data observability via logging, metrics, and alerting tools.

Terraform

  • or similar tools.
  • Connect and orchestrate ingestion from APIs, relational databases, and file systems.
  • Work in agile teams, contributing to standups, retrospectives, and continuous improvement.

What We’re Looking For

  • We believe diverse perspectives and backgrounds lead to better ideas. Even if you don’t meet every requirement, we’d still love to hear from you.
  • Core Experience & Skills

Experience with

cloud-native data engineering using tools such as

  • Databricks, dbt, PySpark, and SQL.
  • Comfort working with at least one major cloud platform
  • (Azure, AWS, GCP) — and openness to others.
  • Hands-on experience with

CI/CD automation, especially with

GitHub Actions or Azure Pipelines.

Strong

  • Python programming skills for transformation, scripting, and automation.
  • Working knowledge of data quality, validation frameworks, and test-driven data development.
  • Familiarity with observability practices including metrics, logging, and data lineage tools.

Understanding of

DataOps concepts, including reproducibility, automation, and collaboration.

Team-first mindset and experience in agile environments

  • (Scrum or Kanban).
  • Professional working proficiency in English (our internal and client-facing working language).

Experience with

  • Snowflake or similar cloud data warehouses.
  • Knowledge of data lineage tools and frameworks.
  • Infrastructure automation using

Terraform, Bash

  • , or
  • PowerShell

Exposure to data modeling techniques like

  • Data Vault or dimensional modeling.
  • Familiarity with

data testing

Understanding of

GxP or other healthcare data regulations.

Experience with

non-relational data systems

  • (e.g., MongoDB, CosmosDB).
  • Spanish and/or Catalan language skills.

Languages

  • English B2 level or higher
  • Spanish and/or Catalan languages a plus

What we offer

  • Hybrid work model and flexible working schedule that would suit night owls and early birds
  • 25 holiday days per year

Free English classes

  • Possibilities of career development and the opportunity to shape the company future
  • An employee-centric culture directly inspired by employee feedback. Your voice is heard, and your perspectives encouraged
  • Different training programs to support your personal and professional development

Work in a fast growing, international company

Friendly atmosphere and supportive Management team.