Leega

Analytics Engineer

• Work for a financial institution, building the data transformation and consumption layer in a Google Cloud environment
• Take data from source to dashboard, ensuring quality, performance, and cost control
• Build, test, and document data transformation models using DBT
• Develop and optimize SQL queries and dimensional and relational models in BigQuery
• Monitor and optimize BigQuery processing performance and costs
• Build, maintain, and orchestrate data pipelines in Airflow
• Develop dashboards and semantic models in Looker Platform
• Gather requirements from business stakeholders and translate them into data solutions
• Conduct root-cause analyses and propose insight-driven solutions
• Document and tag data assets, promoting data governance best practices
• Automate tasks and perform exploratory analyses with Python

Senior Analytics Engineer, DBT, GCP

Data Engineer

• Develop and maintain scalable, efficient data pipelines (ETL/ELT)
• Handle data ingestion, transformation, and delivery in GCP environments
• Build solutions using Databricks (Spark/PySpark)
• Design and evolve data architectures (Data Lake, Data Warehouse, Lakehouse)
• Integrate diverse data sources (APIs, databases, streaming)
• Ensure data quality, governance, and reliability
• Monitor performance and optimize cloud costs
• Collaborate with BI, Analytics, and Data Science teams

Mid-Level GCP Data Engineer

Business Intelligence Developer

• Support the IT Governance team in analytics initiatives and the development of a data-driven culture
• Transform data from multiple sources into high-performance executive, tactical, and operational dashboards
• Develop high-performance executive, tactical, and operational dashboards
• Connect and structure data from multiple sources, including APIs, SQL Server, and Data Lakes
• Define KPIs and metrics aligned with business objectives
• Ensure UX/UI best practices in data visualization
• Implement BI governance, security, and documentation standards

Senior Power BI Developer – Governance

• Serve as a Senior Data Engineer on the collections squad of a large financial institution
• Build and enhance cloud-based data pipelines and models using dbt
• Participate in a data community of practice (chapter) and promote best practices
• Support business teams in advancing their data maturity
• Collaborate continuously with Data Science, BI, Data Engineering, and business teams
• Diagnose issues, propose standards, and document solutions
• Assess data warehouse architecture and requirements
• Map data, transformations, and processes across GCP services
• Define full-load, incremental, and CDC migration strategies
• Develop a data architecture plan on GCP
• Design BigQuery table schemas with performance, cost, and scalability in mind
• Define BigQuery partitioning and clustering strategies
• Model Bronze, Silver, and Gold zones in Cloud Storage
• Create transformations using Dataproc/Spark or Dataflow to load data into BigQuery
• Translate existing business logic and transformations in GCP
• Implement data validation and quality processes
• Use Terraform to provision and manage GCP resources
• Configure and optimize Dataproc clusters
• Manage networking, IAM security, and access controls in GCP
• Optimize BigQuery queries, Spark jobs, and GCP resource utilization
• Implement data security in transit and at rest
• Define and enforce IAM policies and ensure compliance with data governance requirements
• Troubleshoot performance and functional issues affecting pipelines and GCP resources
• Document architecture, pipelines, models, and operational procedures
• Communicate with team members, stakeholders, and other departments
• Ensure clear communication between architecture, software components, and ongoing development efforts

Senior Data Engineer, GCP/dbt

Data Analyst

• Conduct in-depth studies of consumer profiles and market behavior
• Transform complex data into clear, engaging, and persuasive presentations, with a focus on PowerPoint and verbal presentations
• Present and defend recommendations and participate in discussion forums and meetings with executive leadership
• Work closely with UX Designers, applying a product and business perspective focused on customer experience
• Collaborate with multiple teams to understand pain points and propose evidence-based solutions
• Support financial and performance-related decision-making
• Identify opportunities through consumer behavior and market studies
• Transform SQL analyses into persuasive narratives and high-impact business recommendations

Senior Data Analyst, Advanced SQL, BigQuery, Financial Services

Machine Learning Engineer

• Design and build the ML engineering for the pricing engine
• Develop inference serving, training pipelines, and feature engineering for real-time, low-latency models on Ray
• Design chained model pipelines on Ray Serve, including composition, low latency, and update strategies
• Build distributed training pipelines with Ray Train/Data, HPO with Ray Tune, and tenant-specific trained models with resilient checkpointing
• Define and materialize features in the Feast/Redis feature store, ensuring consistency between training and production
• Implement and optimize linear programming and offline RL components of the pricing pipeline
• Monitor modeling drift, validate versions, and deliver explainability with SHAP in partnership with MLOps
• Serve as a technical reference, mentor team members, and define viable, scalable solutions
• Manage handoffs with data scientists, receive data from data engineers, and deliver to the MLOps/Platform team for deployment and operations

Senior Machine Learning Engineer

Data Scientist

• Transform demand, occupancy, and purchasing behavior data into pricing models for thousands of origin-destination pairs and multi-leg routes
• Conduct exploratory and statistical analyses to uncover patterns, develop hypotheses, and guide modeling efforts
• Model demand and no-shows using gradient boosting and time-series methods, correcting for censored-demand bias
• Estimate price elasticity and willingness to pay by segment and route
• Model seat protection and capacity allocation on multi-leg routes, balancing occupancy and revenue
• Design A/B tests and apply causal inference to validate pricing changes and measure uplift
• Ensure model interpretability, including the use of SHAP, to justify pricing decisions to the business and regulators
• Develop cold-start and calibration strategies for routes with limited historical data
• Collaborate with ML engineers, data engineers, and commercial and operations teams
• Formulate hypotheses, validate them with statistical rigor, and influence revenue and margin across millions of trips per year

Senior Data Scientist

• Develop and maintain data pipelines (ETL/ELT) on Google Cloud Platform, following engineering best practices.
• Monitor data loading and quality, ensuring the reliability and availability of data stores.
• Orchestrate data processes using Airflow.
• Support technical data architecture designs and relationships between tables.
• Document pipelines and data models, including entity-relationship models, and manage code versioning through Git.
• Negotiate the scope and timelines of activities directly with the client.
• Understand and apply business rules related to auto insurance claims when developing solutions.
• Represent the coordination team in technical and business forums.
• Share technical and business knowledge with the team.
• Support management in leading the team, spearheading projects, and ensuring delivery timelines and quality.
• Work for a major insurance company, engaging constantly with the client and taking responsibility for the quality and governance of delivered data.

Senior Data Engineer, GCP

• Design, implement, and evolve scalable data pipelines in a GCP environment
• Develop data ingestion, transformation, and delivery processes using GCP architectures
• Define technical standards, best practices, and reusable frameworks for data engineering
• Ensure solution performance, reliability, observability, and scalability
• Develop and maintain analytical data models
• Automate data integration and transformation processes
• Ensure solution SLAs and availability
• Identify opportunities for cost optimization in GCP
• Support data platform migration and modernization initiatives
• Build and optimize solutions using BigQuery, Dataform, Cloud Storage, Pub/Sub, Cloud Composer/Airflow, Dataflow, Cloud Functions, Cloud Run, Looker, and integrated BI tools
• Implement Data Quality, Data Governance, and Data Observability processes
• Ensure compliance with security requirements, Brazil’s LGPD, and corporate policies
• Define data monitoring, auditing, and lineage strategies
• Lead strategic, tactical, and operational data engineering initiatives
• Support and mentor mid-level and junior data engineers
• Participate in architectural decisions, technical reviews, impact analyses, and technical roadmap planning
• Promote best practices in development, version control, documentation, and testing
• Translate business needs into scalable technical solutions
• Work closely with Analytics, BI, Product, and other teams to prioritize initiatives and deliver value
• Support the evolution of the organization’s data strategy

Senior Data Engineer, GCP, Databricks

• Serve as a technical reference for data and automation projects
• Translate business needs into technical solutions, including data modeling, automation, and pipelines
• Design, structure, and document end-to-end solutions
• Develop process automations and optimizations
• Anticipate improvements based on a strong understanding of the business
• Communicate results to technical and non-technical audiences
• Collaborate with multidisciplinary business, engineering, and architecture teams
• Strengthen the Data Analytics team’s technical capabilities in automation, data modeling, and AI solutions
• Support the development of scalable solutions and the continuous improvement of the team’s practices

Senior BI Analyst, Python, SQL

Risk

• Maintain and enhance the Information Security Management System (ISMS), ensuring alignment with ISO 27001 and corporate policies and guidelines
• Lead risk, control, and compliance assessments, recommending corrective, preventive, and continuous improvement actions
• Consolidate, validate, and manage evidence for internal and external audits and certifications, ensuring document traceability
• Prepare for, support, and monitor audits and certifications, coordinating requirements, controls, deadlines, and action plans
• Monitor metrics, risk treatment plans, audit actions, and improvement plans, reporting results to leadership through executive reports and presentations
• Coordinate Change Advisory Committee governance, ensuring the registration, analysis, approvals, communication, and auditable evidence of changes
• Draft, review, and maintain policies, standards, procedures, matrices, and other normative documents related to IT Governance and Information Security
• Assess risks related to critical changes, vendors, and IT processes, balancing continuity, security, costs, contracts, and compliance
• Organize and govern evidence repositories in SharePoint, ITSM tools, or equivalent platforms
• Serve as a technical reference, guiding analysts and relevant teams on governance, security, and compliance practices