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Staff Data Engineer

Reach IT
Department:Data Engineer
Type:REMOTE
Region:EU
Location:Portugal
Experience:Mid-Senior level
Estimated Salary:€50,000 - €80,000
Skills:
PYTHONSQLAIRFLOWSPARKDATABRICKSETLDATA ENGINEERING
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Job Description

Posted on: March 6, 2025

🔵 Reach IT - Nearshore Solution!

Our nearshore expertise sets us apart. We specialize in on-demand, scalable solutions and operational excellence. By bridging the talent gap, we deliver results that drive your business forward.

We’re seeking a Staff Data Engineer- Artificial Intelligence (Portugal)🛡Why This Role?

  • High ownership – You’ll be responsible for designing, maintaining, and evolving our data platform.
  • Be the expert – You’ll shape how data is structured, transformed, and optimized for ML models.
  • Direct impact – Your work will power AI-driven sales recommendations for enterprise users.

Responsibilities:

  • Own and maintain scalable data pipelines using Python, SQL, Airflow, and Spark (Databricks).
  • Develop data ingestion strategies using APIs, Airbyte, and web scraping.
  • Transform and clean data for ML models using Databricks (or Spark-based systems).
  • Optimize storage layers using a Medallion architecture (Bronze/Silver/Gold) approach.
  • Ensure data quality, governance, and observability across all pipelines.
  • Collaborate with ML, AI, and backend teams to integrate data into AI models.
  • Continuously refine and improve how data is structured, stored, and served.

What We’re Looking For ?

  • 5+ years of experience in data engineering with strong Python & SQL expertise.
  • Hands-on experience with Airflow, ETL pipelines, and Spark (Databricks preferred).
  • Experience integrating structured & unstructured data from APIs, CRMs, and web sources.
  • Ability to own and scale data infrastructure in a fast-growing AI-driven company.
  • Strong problem-solving skills and a desire to improve how data is structured for ML.

Bonus Points:

  • Exposure to Golang for API development (not required, but helpful).
  • Experience with MLOps (feature stores, model data versioning, SageMaker, ClearML).
  • Familiarity with Terraform, Kubernetes, or data pipeline automation.
  • Experience in database design to support customer-facing access patterns
Originally posted on LinkedIn

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