Engenheiro(a) de Dados

Accountabilities: Design, build, and maintain scalable and resilient data pipelines for ingestion, transformation, and orchestration of critical business data.

Collaborate with engineering teams, external data providers, and business stakeholders to understand requirements and translate them into efficient data solutions.

Develop and optimize data models to improve storage efficiency, query performance, and data accessibility.

Implement and promote engineering best practices, including code versioning, automated testing, metadata documentation, and data quality validation.

Ensure data consistency, reliability, and governance through robust monitoring, security controls, and lifecycle management processes.

Act as a bridge between engineering, analytics, data science, and business teams, fostering collaboration and enabling data-driven initiatives.

Document processes, workflows, and technical solutions to facilitate transparency and knowledge sharing across teams.

Identify opportunities for continuous improvement in platform architecture, scalability, and operational efficiency.

Requirements:

Solid experience in Data Engineering, with hands-on expertise in building and maintaining end-to-end data pipelines.

Advanced proficiency in SQL, including the ability to create complex and high-performance queries.

Strong knowledge of data modeling principles and best practices for analytical and operational environments.

Experience with orchestration tools such as Airflow, Prefect, Dagster, or similar technologies.

Familiarity with Delta Lake and data versioning strategies for historical data management.

Practical experience with cloud platforms such as AWS, Google Cloud Platform (GCP), or Microsoft Azure.

Knowledge of data security practices, including governance, anonymization, masking, and compliance requirements.

Experience with Git, CI/CD practices, and agile methodologies.

Strong communication and stakeholder management skills, with the ability to work effectively in cross-functional teams.

Nice to have: experience with NoSQL databases (MongoDB, Cassandra, DynamoDB) and exposure to Generative AI, LLMs, or agent-based platforms applied to data solutions.

Benefits:

Profit Sharing Program (PLR).

Medical and dental insurance.

Life insurance coverage.

Flexible meal and food allowance package.

Optional transportation voucher.

Childcare assistance.

Extended parental leave policies.

Wellness and quality-of-life partnership programs.

Birthday day off.

Discounts and benefits related to education, food, and lifestyle services.

Opportunity to grow in a dynamic and innovative environment alongside highly skilled professionals.

Inclusive workplace committed to diversity and equal opportunities.

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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