Senior Data Architect

About the opportunity A Brazilian technology company with a strong growth trajectory is hiring a Data Architect. The Data Engineering team supports a suite of custom applications built on state-of-the-art data technologies, enabling applied science behind clean beauty products, bio-based renewable chemicals and vaccine ingredients.

Recruitment process managed by BM Vagas.

Position overview The Data Architect will define and implement the vision for the company's enterprise data architecture, setting the technical standards and design patterns that other engineers build upon. This person will own architecture design, engineering, security and resiliency across all data environments, serving as the primary technical authority for data platform decisions, and will support management functions as a point of contact for technical needs.

The ideal candidate has deep, hands-on experience in cloud and on-prem database technologies and can independently lead architecture design across projects ranging from simple to highly complex, cross-system initiatives.

Key responsibilities

Data strategy and stakeholder management

• Define, own and implement the enterprise data architecture strategy and roadmap with stakeholders and leadership
• Establish and govern data architecture standards, patterns and best practices across all data platforms, and lead architecture design reviews for new and existing systems
• Act as the point of contact for internal partners, delivering robust solutions for technical data needs, databases, BI, analytics, reporting and ETL

Data architecture and engineering

• Design and document data architecture, including upstream and downstream systems, to create a full view of data flow and design
• Develop and document strategies for POCs and the onboarding of new products into the data framework
• Automate processes and configure tools for operational tasks such as maintenance automation, monitoring, security auditing and compliance
• Architect hybrid OLTP topologies spanning on-premises PostgreSQL and MSSQL Server clusters and Google managed database services, ensuring consistent performance, security and failover behavior
• Design and implement heterogeneous data replication strategies to keep on-prem and cloud OLTP systems, and downstream analytical systems, in sync
• Design dimensional models (star and snowflake schemas, slowly changing dimensions, conformed dimensions) for enterprise data warehousing in BigQuery
• Define and enforce data governance and MDM standards, including metadata management and data cataloging strategy, in partnership with data stewards
• Establish and advocate for infrastructure-as-code practices (Terraform) and CI/CD automation for provisioning and managing data platform environments

Technical implementation and maintenance

• Ensure monitoring protocols that capture, audit and alert on deviations
• Document all data, business rule and metric changes for team members, executives and power users
• Develop a strategy for installation, configuration, monitoring, high availability and disaster recovery
• Support ongoing work related to API management, BI, middleware and publishing

Team leadership and mentorship

• Mentor junior team members, providing technical guidance for onboarding and growth
• Lead and support engineering initiatives as a technical leader within the team
• Serve as the escalation point and technical authority for architecture decisions across the Data Engineering team

Innovation and research

• Spend 5 to 10% of the time researching new data products and technologies

Requirements

• Education: Master's degree or higher in Computer Science, Information Technology or a related field, or equivalent practical experience. Relevant cloud architecture certifications (Google Professional Data Engineer or Cloud Architect) are a plus
• Experience: 12+ years in data engineering and architecture, including at least 3 years in a data architect or lead architecture capacity, or an equivalent combination of post-bachelor's education and experience
• Proven experience as a Data Architect or Senior Data Engineer moving into an architecture-focused role, with a track record of leading complex, cross-system design initiatives independently
• Professional written and verbal fluency in English, the working language of the global engineering teams and technical documentation

Required skills

• Deep expertise in data modeling and design of transactional and analytical systems
• Advanced SQL and administration of RDBMS: PostgreSQL, SQL Server, BigQuery
• Expertise in cloud environments (GCP, AWS, Azure), with exposure to multiple cloud architectures
• Architectural design and management experience of hybrid cloud and on-premises data topologies
• Experience with heterogeneous replication between data sources for OLTP and OLAP workloads
• Hands-on experience with ETL tools such as dbt, SSIS, Airflow and PySpark, with ETL/ELT best practices at scale
• Programming skills in Python (preferred), Java or Scala
• Experience with data cataloging and annotation tools such as Alation or Dataplex
• Experience designing and implementing data lake and data warehouse architectures using modern cloud solutions
• Hands-on experience with BI, analytics and visualization tools (PowerBI, Spotfire, Tableau, JMP, Metabase)
• Experience with monitoring and alerting tools (Prometheus, Grafana, DataDog, Nagios)

Soft skills

• Able to work with minimal direction and on multiple projects simultaneously
• Ability to build and maintain strong relationships with business users, software developers and cross-functional teams
• Strong written and verbal communication, translating between technical and non-technical stakeholders
• Ability to work both independently and with a global team

Preferred qualifications

• Migration of large PostgreSQL databases from self-hosted solutions to cloud managed services
• Data governance and MDM frameworks, including metadata management and enterprise data cataloging strategy
• Modern Google Cloud solutions: BigQuery, Cloud Composer / Apache Airflow, DataStream
• Strong dimensional modeling: star and snowflake schemas, slowly changing dimensions, conformed dimensions
• Test Data Management methodologies and tools for provisioning isolated non-production environments
• Infrastructure-as-code (Terraform) and CI/CD automation for data platform environments

Additional information Responsibilities may grow as the team takes on additional work, particularly in API management, BI, middleware and publishing.

Working hours require partial overlap with US Pacific Time to align with the global team.

Work model

• Based in the city of São Paulo: hybrid, two days per week in Morumbi
• Based elsewhere in the state of São Paulo: on site in Morumbi every two weeks
• Based outside the state of São Paulo: fully remote

Contract Independent contractor (PJ), Brazil-based candidates only.