AWS Data Specialist

Jobgether; Brasil; Híbrido; BRL 180 000 - 300 000; Tempo integral

Vantagens oferecidas por esta oferta de emprego

Health insurance

Meal/food allowance

Childcare assistance

Extended parental leave

Wellness programs (Gympass/TotalPass)

Profit-sharing (PLR)

Life insurance

Learning platform access

Language-learning platform

Remote work option with Campinas-area辦

Resumo da oferta

Jobgether is seeking an AWS Data Specialist based in Brazil to join a data engineering team. You will design, optimize, and maintain modern data pipelines on AWS, contributing to cloud migration and advanced data architectures.

You will work across ETL/ELT, data platforms, governance, observability, and large-scale processing, with exposure to Generative AI and AI agents where relevant to business objectives.

Qualificações

• Proven professional experience in data engineering with hands-on AWS data ecosystem work.
• Strong knowledge of AWS data services (Glue, EMR, Athena, DynamoDB, Lake Formation, S3, EventBridge).
• Solid experience with Apache Spark and PySpark for large-scale processing.
• Experience with data warehouse concepts and modern architectures (Redshift, Lakehouse, Iceberg/Delta).
• Hands-on with Airflow, relational/NoSQL databases, and SQL.
• Understanding of data governance, lineage, and observability (OpenLineage, CloudWatch, Datadog).
• DevOps mindset with incident troubleshooting and cost-performance trade-offs.
• Strong collaboration and communication across multidisciplinary teams.

Responsabilidades

• Plan and execute migration of systems and large data volumes to AWS cloud.
• Design, develop, and optimize robust ETL/ELT pipelines with data integrity and performance.
• Build scalable data architectures using AWS services and modern storage tech.
• Collaborate with product, operations and development teams to deliver data solutions.
• Monitor data environments and pipelines; investigate incidents and improve reliability.
• Create documentation on architecture, lineage, and procedures.
• Apply governance and observability practices to ensure transparency and quality.
• Participate in capacity planning and cost-performance decisions.
• Promote DevOps, automation, and continuous improvement in data workflows.
• Explore emerging technologies in Generative AI and advanced data architectures when relevant.

Conhecimentos

AWS Glue

EMR

Amazon Athena

DynamoDB

Lake Formation

Amazon S3

EventBridge

Apache Spark

PySpark

Redshift

Iceberg/Delta

Airflow

SQL/NoSQL

OpenLineage/Observability

CloudWatch/Datadog

DevOps & automation

RAG/AI concepts

Ferramentas

PySpark

Airflow

SQL

Descrição da oferta de emprego

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for an AWS Data Specialist based in Brazil.

Join a data engineering team focused on building robust, scalable cloud data solutions on AWS. In this role, you will design, optimize, and maintain modern data pipelines while contributing to cloud migration and advanced data architecture initiatives. You will work across ETL/ELT, data platforms, governance, observability, and large-scale data processing. The role also provides exposure to emerging technologies such as Generative AI, AI agents, and advanced data architectures. You will collaborate with multidisciplinary teams to turn complex data requirements into reliable and efficient solutions. This is an opportunity to contribute to technically challenging projects while driving automation, performance, and continuous improvement.

Accountabilities:

• Plan and execute the migration of systems and large volumes of data to modern AWS cloud infrastructure.
• Design, develop, optimize, and orchestrate robust ETL/ELT pipelines while ensuring data integrity, quality, reliability, and performance.
• Build and maintain scalable data architectures using AWS services and modern processing and storage technologies.
• Work closely with development, product, operations, and other multidisciplinary teams to deliver efficient and sustainable data solutions.
• Monitor data environments, pipelines, and databases, investigate complex incidents, and implement solutions that improve reliability and operational performance.
• Create and maintain technical documentation covering architecture, data lineage, processes, and operational procedures.
• Apply data governance and observability practices to improve transparency, quality, and maintainability across data environments.
• Contribute to capacity planning and technical decisions by evaluating cost, scalability, and performance trade-offs.
• Promote DevOps principles, automation, and continuous improvement throughout data engineering workflows.
• Explore and support the adoption of emerging technologies in Generative AI and advanced data architectures where relevant to business and technical objectives.

Requirements:

• Proven professional experience in data engineering, with strong hands-on expertise designing and implementing solutions within the AWS data ecosystem.
• Strong knowledge of AWS data services, including AWS Glue, EMR, Amazon Athena, DynamoDB, Lake Formation, Amazon S3, and EventBridge.
• Solid experience with Apache Spark and PySpark for large-scale data processing.
• Experience with data warehouse and modern data architecture concepts, including Amazon Redshift, Lakehouse architectures, Open Table Formats such as Iceberg or Delta, data contracts, and schema evolution.
• Practical experience with Apache Airflow and strong knowledge of relational databases and SQL, as well as NoSQL technologies.
• Understanding of data governance, data lineage, and observability practices, including OpenLineage, CloudWatch, or Datadog.
• Strong DevOps and automation mindset, with the ability to troubleshoot incidents, improve processes, and balance cost against performance and scalability.
• Ability to collaborate effectively with multidisciplinary teams and communicate technical concepts clearly.
• Strong planning, analytical, and problem-solving skills, with a proactive approach to continuous improvement.
• Experience with Amazon Bedrock, MCP Server, AI agents, prompt engineering, RAG, embeddings, guardrails, evaluation frameworks, or Spec-Driven Development is a strong advantage.
• Previous experience with SAS or large-scale legacy system migration projects is desirable.
• Active AWS or related data-platform certifications are considered a plus.

Benefits:

• Health and dental insurance.
• Meal and food allowance.
• Childcare assistance.
• Extended parental leave.
• Access to fitness, health, and wellness programs through Wellhub (Gympass) and TotalPass.
• Profit-sharing program (PLR).
• Life insurance.
• Continuous learning opportunities through a dedicated learning platform.
• Discounts through partner programs.
• Free online platform focused on physical health, mental health, and overall well-being.
• Pregnancy and responsible parenthood courses.
• Partnerships with online learning platforms.
• Language-learning platform.
• Additional employee benefits and development opportunities.
• Remote work opportunity, with office attendance requirements applicable to employees residing in the Campinas metropolitan region under the relevant workplace policy.
• A strong focus on inclusion, accessibility, employee well-being, and professional development.

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!

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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