• Migrate data and analytics workloads from BigQuery to Snowflake • Support GCP to AWS data platform migration • Develop and optimize ETL/ELT pipelines using Python and SQL • Build analytics-ready datasets for reporting and dashboards • Support BI tools such as Looker, Amazon QuickSight, or Tableau • Ensure data quality, performance, and reliability • Collaborate with data architects, analytics, and DevOps teams

• Define and lead end-to-end data architecture for complex ecosystems, balancing technical depth with business outcomes. • Translate business strategy into scalable technology solutions through discovery workshops, assessments, and roadmaps. • Act as technical sponsor for CI&T’s most strategic accounts, working closely with C-level clients and non-technical stakeholders. • Lead architectural design, technology selection, and proof-of-concepts for critical platforms and innovation programs. • Govern technical quality across delivery squads, driving adherence to security, performance, scalability, and privacy standards. • Support pre-sales, proposal development, RFPs, and technical visioning with account teams and clients. • Coach and mentor senior architects and technical leads, shaping technical career development paths.

• Design, build, and maintain scalable, high-quality data pipelines for structured and unstructured data. • Implement robust data ingestion, transformation, and storage using cloud-based technologies. • Collaborate with stakeholders to understand business goals and translate them into data engineering solutions. • Monitor, troubleshoot, and optimize data pipelines for reliability and performance. • Support data validation, testing, and documentation processes. • Contribute to the design and deployment of modern data architectures (e.g., data lakes, lakehouses, data warehouses). • Apply Infrastructure-as-Code (IaC) practices for provisioning and managing cloud resources. • Integrate emerging tools and frameworks to modernize existing data environments. • Ensure security, governance, and compliance in all stages of data handling. • Work in agile teams, contributing to continuous improvement and mentoring junior team members.

• Design, build, and support large-scale backend data pipelines on cloud data platforms (GCP/BigQuery) • Lead development and evolution of semantic layers, including universal / reusable semantic models that support multiple business domains and analytics tools • Design and maintain Analytical Data Store (ADS) data structures optimized for analytics, reporting, and advanced modeling. • Partner with multiple EDW product teams to ensure consistent data modeling, metric definitions, and access patterns • Drive platform reliability, scalability, and operational excellence across data products • Lead query performance tuning and cost optimization efforts (slot usage, partitioning, clustering, aggregates, workload management) • Support and modernize data orchestration frameworks • Implement and enforce data quality, validation, and monitoring frameworks • Perform deep root-cause analysis of data issues, pipeline failures, and performance regressions • Contribute to technical roadmaps, refactoring strategies, and platform modernization initiatives • Mentor and grow other engineers through design reviews, code reviews, and technical guidance • Create and maintain architecture diagrams, standards, and technical documentation