Analista de Engenharia de Dados Sênior - Vaga Afirmativa para Mulheres

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Analista de Engenharia de Dados Sênior - Vaga Afirmativa para Mulheres based in Brazil.

As a Senior Data Engineering Analyst, you will join a Data Office environment focused on building complex data flows and highly resilient pipelines. You will play a key role in modernizing legacy processes and transitioning them toward scalable, cloud-based architectures. The position combines large-scale data processing, data product development, and complex data transformations using modern cloud technologies. You will also contribute to data quality initiatives through monitoring solutions, dashboards, and reliable data flows. Working closely with product teams and business stakeholders, you will translate requirements into robust and efficient technical solutions. This is an opportunity to work on high-impact data challenges while continuously improving performance, governance, observability, and cost efficiency.

Accountabilities:: Develop and maintain scalable, efficient, and resilient data pipelines using PySpark and distributed processing frameworks.

Modernize legacy data processes by migrating them to scalable distributed-processing architectures.

Design and implement data processing solutions within AWS environments, leveraging appropriate cloud services.

Build and evolve Data Products and implement complex data transformations across large-scale datasets.

Support data quality initiatives by developing monitoring applications, dashboards, and the underlying data flows required to enable these solutions.

Work with large-scale data ingestion, cleansing, prioritization, and transformation processes.

Collaborate with product teams, data analysts, and other stakeholders to understand business requirements and translate them into effective data solutions.

Optimize data architectures with a focus on performance, governance, scalability, reliability, and cost efficiency.

Contribute to automation, observability, and continuous improvement initiatives across data engineering processes.

Support the evolution of data platforms and contribute to the adoption of modern engineering practices and technologies.

Requirements

Bachelor's degree or equivalent higher education.

Solid professional experience with PySpark and distributed data processing frameworks.

Strong knowledge of Apache Airflow, Apache Spark, and Hadoop where applicable.

Proficiency in programming languages, particularly Python.

Hands-on experience with relevant AWS services, such as EMR, Lambda, DynamoDB, and S3; experience with AWS Glue is a plus.

Good knowledge of SQL databases and data processing concepts.

Familiarity with DevOps practices, CI/CD pipelines, and modern software delivery processes.

Experience provisioning infrastructure through Infrastructure as Code (IaC) is a plus.

Experience working with agile methodologies is desirable.

Previous experience migrating legacy processes to distributed data architectures is an advantage.

Applied knowledge of Machine Learning and AI Agent Architecture is a plus.

Strong analytical skills and the ability to understand and translate complex business rules into technical solutions.

Critical thinking, a strong focus on efficiency, and a mindset oriented toward optimization and continuous improvement.

Clear communication and effective collaboration with stakeholders from different technical and business areas.

Results-oriented mindset, fast learning ability, and adaptability to evolving technologies.

This is an affirmative-action opportunity for women, created as part of the organization's commitment to advancing gender equity in the workplace.

Benefits

Opportunities to work with large-scale data platforms and modern cloud technologies.

Exposure to complex data engineering challenges involving distributed processing, cloud migration, data products, and data quality.

Continuous learning and professional development opportunities.

An inclusive environment focused on diversity, collaboration, and professional growth.

Access to initiatives supporting women's development, leadership, networking, and career advancement.

Participation in communities and programs designed to promote greater gender equity and diverse perspectives.

Opportunities to collaborate with multidisciplinary teams and stakeholders across different areas of the business.

A culture focused on innovation, continuous improvement, and meaningful impact through data and technology.

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.     #LI-CL1