
Staff Data Engineer
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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