Consultor de Dados – Engenharia & Ciência de Dados

BrazilRemoteFull-timemid

Other

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Quick Summary

Key Responsibilities

Design, model, and structure data environments using Microsoft Azure services. Build, maintain, and optimize data pipelines to support efficient data ingestion and transformation.

Requirements Summary

Hybrid professional background combining Data Engineering and Data Science. Experience working with Microsoft Azure, particularly Data Lake, Synapse, Databricks, or related services.

Technical Tools

Other

We are looking for a Data Consultant with expertise spanning Data Engineering and Data Science to help design and evolve modern data environments.
In this role, you will work primarily within the Azure ecosystem, building scalable data architectures and reliable pipelines.
You will contribute to the development and optimization of Data Lake, Synapse, and Databricks environments.
Your work will ensure that data is properly ingested, transformed, structured, and made available for analytical use.
Combining technical expertise with strong analytical thinking, you will translate business needs into practical, data-driven solutions.
This is a fully remote, long-term opportunity for a professional who enjoys solving complex challenges and generating measurable business value.

You will contribute to the architecture, modeling, and continuous improvement of data environments, ensuring data quality, organization, and availability. Your responsibilities will include:

Design, model, and structure data environments using Microsoft Azure services.
Build, maintain, and optimize data pipelines to support efficient data ingestion and transformation.
Develop and evolve data architectures based on Azure Data Lake, Synapse, Databricks, and related services.
Organize data into structured layers to improve accessibility, consistency, and usability.
Apply conceptual, logical, and physical data modeling practices.
Ensure data quality, reliability, and availability across the data environment.
Collaborate with business stakeholders to understand analytical needs and translate them into technical data solutions.
Apply both Data Engineering and Data Science perspectives to deliver solutions aligned with operational and business objectives.

Requirements

~1 min read

The ideal candidate combines hands-on Data Engineering experience with analytical capabilities and a strong understanding of business needs. The following qualifications are expected:

Hybrid professional background combining Data Engineering and Data Science.
Experience working with Microsoft Azure, particularly Data Lake, Synapse, Databricks, or related services.
Practical experience in conceptual, logical, and physical data modeling.
Experience designing and building data pipelines.
Knowledge of data environment architecture, including data ingestion, transformation, and layered organization.
Strong analytical skills and business awareness, with the ability to translate departmental requirements into data-driven technical solutions.
English proficiency is considered an advantage.

What We Offer

~1 min read

✓Learning and development incentives, including access to Udemy.

✓Corporate English classes at affordable rates.

Fully remote work model.
Independent contractor (PJ) arrangement.
Long-term engagement with an indefinite duration.

How Jobgether works:

We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.

We appreciate your interest and wish you the best!

Why Apply Through Jobgether?

Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.

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