Especialista de Plataforma de Dados I

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 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.