Senior Data Pipeline Specialist

3 semanas atrás

Brasil beBeeDataEngineer Tempo inteiro

Transforming global data to drive business forward.

A strategic Data Engineer is required to build, maintain, and modernize complex data pipelines processing large-scale regulatory information from around the world.

The successful candidate will work with Python, SQL, and related tools to untangle legacy code, migrate processes to maintainable platforms like Airflow, and ensure accurate, reliable data for downstream applications and APIs.

This role requires a strong technical ability and consulting mindset – able to learn undocumented systems, troubleshoot gaps, and design forward-looking solutions that will scale as our data environment evolves.

Key Responsibilities:

  • Design and implement efficient data pipelines using Python and related tools.
  • Migrate legacy code to more maintainable platforms ensuring seamless integration.
  • Ensure data accuracy, reliability, and usability for downstream applications and APIs.
  • Leverage strong technical skills and consulting mindset to drive data transformation and deliver high-quality results.

Requirements:

  • 7+ years of experience in analyzing, extracting, creating, and transforming large datasets using Python.
  • Proficiency in Python 3+, Pandas, NumPy, Jupyter Notebooks, and common Python libraries and tools for data engineering.
  • Deep experience with SQL and relational data using Oracle, Postgres, or MS SQL Server.
  • Solid understanding of database design principles, data modeling, and data warehousing concepts.
  • Excellent troubleshooting skills and instincts.
  • Curious, self-motivated, and self-directed; comfortable working within an Agile software development team with short, iterative delivery cycles.
  • College degree or equivalent experience in computer science, software development, engineering, information systems, math, or other applicable field of study.

PREFERRED QUALIFICATIONS:

  • Experience with NoSQL databases such as MongoDB, AWS DynamoDB, or Azure Cosmos DB.
  • Familiarity with cloud platforms (e.g., AWS, Azure, GCP) and services related to data storage/processing.
  • Exposure to Terraform or other Infrastructure-as-Code tooling.
  • Proficient in Azure DevOps for source code and pipeline management.

Benefits:

  • Opportunity to work on complex data engineering projects.
  • Collaborative and dynamic work environment.
  • Professional growth and development opportunities.

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