Especialista de Plataforma de Dados I

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Especialista de Plataforma de Dados I based in Brazil.

This is a senior technical role focused on shaping and evolving a modern data platform at scale.

You will act as a technical reference across multiple data teams, influencing architecture, engineering standards, and platform strategy.

The role spans ingestion, processing, data quality, observability, analytics, and large-scale data availability.

You will balance scalability, resilience, performance, and cloud infrastructure costs while solving complex technical challenges.

A key focus will be turning the data platform into an internal product that enables greater self-service and reduces friction for consuming teams.

You will also mentor engineers and collaborate closely with Product, Software Engineering, Infrastructure, Security, and Commercial stakeholders.

This is an opportunity to make a broad technical impact in a data-intensive environment while helping modernize and strengthen critical data capabilities.

Accountabilities

• Act as a technical reference across multiple Data teams, promoting engineering consistency and technical excellence while aligning platform evolution with broader product and technology objectives.
• Lead end-to-end data architecture decisions covering lakehouse, data warehouse, streaming, batch processing, and real-time processing, with a focus on cost, performance, scalability, and resilience.
• Drive the evolution of large-scale ingestion, capture, processing, data-quality, and data-delivery pipelines.
• Ensure the operational health of critical pipelines through clear SLAs, comprehensive observability, logging, metrics, data-quality monitoring, lineage, and mature troubleshooting practices.
• Evolve the Data Platform as an internal product by expanding self-service capabilities, reducing ingestion friction, and standardizing engineering practices for consuming teams.
• Identify and address structural bottlenecks involving infrastructure costs, ingestion times, data quality, technical debt, and organizational silos, with a medium- and long-term perspective.
• Mentor engineers and developers at different levels, encouraging technical growth, knowledge sharing, and adoption of engineering best practices.
• Serve as a key technical point of contact for Data across Product, Software Engineering, Infrastructure/SRE, Security, and Commercial teams.
• Provide technical leadership in complex initiatives and guide architectural decisions in environments involving ambiguity and multiple stakeholders.

Requirements

• Proven experience leading highly complex projects involving the development or evolution of data platforms.
• Strong technical background in Data Engineering, with hands-on experience designing and operating large-scale ETL/ELT ingestion and processing pipelines.
• Practical experience with technologies such as Databricks, Spark, Kafka, and Mage/Airflow, with the ability to discuss architectural decisions in depth.
• Strong knowledge of modern analytical architecture paradigms, including lakehouse, data warehouse, streaming, batch processing, open data formats such as Parquet, Iceberg, and Delta, and analytical data modeling patterns.
• Ability to make and communicate sound technical decisions in ambiguous environments while aligning multiple stakeholders.
• Experience designing observability strategies, including metrics, alerts, dashboards, and monitoring for complex systems.
• Excellent written and verbal technical communication skills, with the ability to influence, align, and collaborate effectively across teams.
• Strong understanding of cloud analytics infrastructure costs, processing optimization, and trade-offs between managed and in-house solutions.
• Experience working with SaaS B2B businesses, particularly data-intensive industries such as supply chain, retail, fintech, ad-tech, or telecommunications, is a plus.
• Experience with customer-facing data products, rather than exclusively internal analytics environments, is desirable.
• Exposure to integrating AI/ML capabilities into an existing data platform is an advantage, even without direct ownership of MLOps.
• Experience with analytical-stack modernization programs, such as migrations from legacy platforms to lakehouse architectures, is beneficial.
• Knowledge of Data Governance and Data Quality practices is a plus.
• Relevant cloud certifications or training in AWS, GCP, or Azure, as well as governance frameworks such as DAMA-DMBOK or DCAM, are desirable.

Benefits

• Fully remote or hybrid work options for professionals residing in Brazil.
• Flexible working hours.
• Health insurance, dental insurance, and life insurance, with coverage extendable to eligible dependents.
• Medication assistance, including coverage for children according to the applicable policy.
• Transportation allowance or parking assistance for employees living in cities where offices are available.
• Flexible meal and food allowance.
• Wellhub and TotalPass wellness benefits.
• Birthday day off, with the flexibility to choose the day.
• Parental support through a dedicated program for new mothers and fathers.
• Extended parental leave of up to 6 months for mothers and 30 days for fathers.
• Childcare assistance according to company policy.
• Access to external learning and professional development through the Unico Skill program.
• Referral bonuses and additional recognition programs.
• Opportunities to work with large-scale data, technology, and analytics challenges in a collaborative environment.
• Inclusive workplace committed to diversity, belonging, and professional growth.