Senior Data Developer (Analytics Engineer)
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Senior Data Developer (Analytics Engineer)
Location
Brazil
Experience
Senior
Posted
Jul 10, 2026
Apply by
August 9, 2026
Applicants
0
Early applicantEasy applyFull-timeWork from Home
Job Description
This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Data Developer (Analytics Engineer) based in Brazil.
This role offers the opportunity to design and deliver impactful data products that power analytics, AI solutions, and strategic business decisions.
The professional will act as a bridge between business and technology, transforming complex requirements into scalable and reliable data solutions.
You will own the full lifecycle of data products, from ingestion and modeling to validation, optimization, and delivery.
The position requires strong technical expertise combined with business understanding, proactive problem-solving, and stakeholder communication skills.
You will collaborate with data, AI, and business teams to create high-quality datasets that enable innovation and smarter decision-making.
This is a senior-level opportunity in a global, technology-driven environment focused on building meaningful solutions through data and artificial intelligence.
### Accountabilities:
- Engage with business stakeholders to understand challenges, objectives, and requirements, translating business needs into clear technical specifications.
- Own the complete lifecycle of data products, including data ingestion, modeling, transformation, validation, delivery, and ongoing monitoring.
- Design and implement scalable data transformation layers that apply business rules and prepare datasets for analytics and AI applications.
- Develop and maintain data pipelines from multiple sources using SQL, Python, and modern data engineering practices.
- Build structured and reliable datasets, data dictionaries, and models to support AI initiatives and intelligent reporting capabilities.
- Implement data quality processes, automated validations, testing routines, and monitoring mechanisms to ensure accuracy and integrity.
- Act as a guardian of data reliability by ensuring metrics, KPIs, and analytical outputs accurately represent business needs.
- Collaborate with AI teams to prepare and optimize data structures for machine learning and generative AI applications.
- Proactively identify improvement opportunities, challenge existing approaches, and propose innovative solutions.
- Communicate technical concepts clearly to technical and non-technical stakeholders, supporting alignment and informed decision-making.
- Document data models, architecture decisions, and solution approaches to ensure scalability and knowledge sharing.
- Deliver high-quality data solutions in agile environments while balancing speed, flexibility, and technical excellence.
## Requirements:
- Proven experience working as a Senior Data Engineer, Analytics Engineer, or similar data-focused role.
- Advanced proficiency in SQL and Python for data analysis, transformation, automation, and validation.
- Strong experience with data modeling concepts and data warehouse architecture.
- Hands-on experience with BigQuery or other cloud-based data warehouse platforms.
- Ability to understand complex business logic and validate solutions from a business perspective, beyond purely technical requirements.
- Strong ownership mindset with a proactive approach to identifying improvements and driving solutions independently.
- Experience defining and preparing data requirements for AI or machine learning applications.
- Track record of delivering high-impact data projects with quality and efficiency.
- Advanced or fluent English skills across reading, writing, and conversation, with experience collaborating with international stakeholders.
- Experience with dbt (data build tool) for transformation and analytical pipeline orchestration is a plus.
- Familiarity with data ingestion tools such as Airbyte or Airflow is desirable.
- Knowledge of automated testing practices and CI/CD approaches for data pipelines is considered an advantage.
- Experience in Supply Chain, Retail, Consumer Goods, or similar industries is a plus.
- Previous experience preparing data for generative AI, conversational analytics platforms, or advanced reporting solutions is desirable.
- Experience creating business-oriented analytical reports, dashboards, or custom visualizations is a plus.
## Benefits:
- Health and dental insurance.
- Meal and food allowance.
- Childcare assistance.
- Extended paternity leave.
- Gym partnerships and access to health and wellness professionals through Wellhub and TotalPass.
- Profit Sharing and Results Participation (PLR).
- Life insurance coverage.
- Continuous learning opportunities through internal education platforms.
- Access to discount programs and partner benefits.
- Online platform focused on physical, mental, and overall well-being.
- Pregnancy and responsible parenting support programs.
- Partnerships with online learning platforms.
- Language learning platform access.
- Opportunities for professional growth in a global technology environment.
- Inclusive culture supported by dedicated health, well-being, and inclusion initiatives.
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?](https://jobgether.com/how-jobgether-works)
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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Key Responsibilities
- Engage with business stakeholders to translate needs into technical specifications.
- Own the complete lifecycle of data products including ingestion, modeling, transformation, validation, and delivery.
- Design and implement scalable data transformation layers for analytics and AI applications.
- Develop and maintain data pipelines using SQL, Python, and modern data engineering practices.
- Build structured datasets, data dictionaries, and models to support AI initiatives.
- Implement data quality processes, automated validations, and monitoring mechanisms.
- Collaborate with AI teams to prepare and optimize data structures for machine learning.
- Communicate technical concepts to technical and non-technical stakeholders.
- Document data models, architecture decisions, and solution approaches.
- Deliver high-quality data solutions in agile environments.
Skills Required
SQLPythonData modelingData warehouse architectureBigQueryCloud-based data warehouse platformsBusiness understandingProactive problem-solvingStakeholder communicationOwnership mindsetCollaborationdbtAirbyteAirflowAutomated testingCI/CDGenerative AI data preparationConversational analytics platformsDashboard creationCustom visualizations
Benefits
- Health and dental insurance
- Meal and food allowance
- Childcare assistance
- Extended paternity leave
- Gym partnerships and access to health and wellness professionals
- Profit Sharing and Results Participation (PLR)
- Life insurance coverage
- Continuous learning opportunities
- Access to discount programs and partner benefits
- Online platform focused on physical, mental, and overall well-being
- Pregnancy and responsible parenting support programs
- Partnerships with online learning platforms
- Language learning platform access
- Opportunities for professional growth
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