Data at Brex

Our Scientists and Engineers work together to make data — and insights derived from data — a core asset across Brex. But it's more than just crunching numbers. The Data team at Brex develops infrastructure, statistical models, and products using data. Our work is ingrained in Brex's decision-making process, the efficiency of our operations, our risk management policies, and the unparalleled experience we provide our customers.

What You’ll Do

As a Data Engineer at Brex, you will be a core contributor in transforming raw data into actionable insights for various departments across the organization. You'll collaborate closely with Data Scientists, Software Engineers, and business units to create efficient data models, pipelines, and analytics frameworks that drive the business forward. You also play a leading role in the design, implementation, and maintenance of Core Data tables, our high-quality, curated data source for a wide range of analytic applications. 

Where you’ll work

This role will be based in our Sao Paulo office. We are a hybrid environment that combines the energy and connections of being in the office with the benefits and flexibility of working from home. We currently require a minimum of three coordinated days in the office per week, Monday, Wednesday and Thursday. As a perk, we also have up to four weeks per year of fully remote work!

Responsibilities:

• Design, build, and maintain data models and pipelines that scale with the growing number of services, products, and changes in the company.
• Collaborate closely with Data Scientists, Data Analysts, and Business teams to understand their data needs, translating them into robust, efficient, scalable data solutions that enable ease of predictive analytics, data analysis, and metrics formulation. 
• Maintain data documentation and definitions, building and ensuring that source-of-truth tables remain high quality for data science and reporting applications. 
• Develop and enable integration with various data sources, allowing for more data-driven initiatives across the company.
• Apply best practices in data management to ensure the reliability and robustness of data utilized across various analytics applications.
• Set and proliferate company-wide standards for data relating to structure, quality, and expectations.
• Act as a liaison between the technical and non-technical teams, bridging gaps and ensuring that data solutions align with business objectives.
• Use agentic AI where it speeds up pipeline and quality work, without skipping validation.

Requirements:

• 3+ years of experience in Data Engineering, Data Analytics, or a related field such as Analytics Engineering.
• Advanced knowledge of databases and SQL with the ability to efficiently stage, process, and transform data.
• Experience integrating and orchestrating data workflows with various modern data tools and systems.
• Experience with data modeling, ETL/ELT processes, and data warehousing solutions.
• Experience working with a data warehouse such as Snowflake.
• Experience with a data workflow orchestrator tool such as Airflow.
• Experience with a programming language such as Python. 
• Experience with agentic AI. 
• Exceptional quantitative and analytical skills.
• Strong communication skills and ability to collaborate with various stakeholders, both technical and non-technical.

Nice to have:

• Familiarity with BI tools such as Looker, Tableau, or similar platforms. 
• Solid dbt in production: models, tests, docs, and collaboration in a shared repo. 
• AI-ready data: Metrics and dimensions are clear and reusable so AI-assisted analysis does not fork definitions. 
• Experience with Salesforce data integration. 

Brex LLC is a wholly owned subsidiary of Capital One, N.A.

Brazil, Londrina

At Platform Science, we’re working to connect everything that moves.

Founded in 2015, we are an open IoT platform that partners with innovative fleets, application developers, vehicle manufacturers, and equipment providers in the transportation industry to deliver revolutionary solutions to supply chain professionals across the globe.

Our employees are an engaging, diverse group of people who believe in the power of great ideas. We hire people with different experiences and perspectives to build a company culture that fuels growth through innovation.

We value thoughtful actions and empathy for others. We approach challenges with resiliency and creativity, while encouraging transparency because, no matter our backgrounds or responsibilities, we are one team.

What You’ll Do:

• Leverage our modern data stack (dbt, Snowflake, Looker, PowerBI) in order to identify, analyze, and interpret trends or patterns in complex data sets to enable business-critical decisions
• Work closely with our product and engineering teams to define, build, and analyze meaningful KPIs for our applications and systems
• Apply your expertise in quantitative analysis, data visualization and data-mining to create data alerts and derive actionable insights
• Filter, clean, and transform data from a variety of sources in order to enable analysis
• Work with management to prioritize business and information needs
• Locate and define new process improvement opportunities

What We’re Looking For:

• 3+ years of experience as a data analyst 
• 3+ years of experience with reporting and visualization tools such as Looker, Domo, PowerBI, SSRS, etc
• Advanced SQL skills including multiple-table joins, unions, sub-queries, CTE, aggregations, temporary tables, and analytical functions
• Technical expertise regarding all things data, including: mining, modeling, transforming, cleansing, and validating
• Ability to take vague requests and transform them into concise deliverables
• Strong analytical skills with the ability to collect, organize, analyze, and disseminate significant amounts of information with attention to detail and accuracy

What Would Be Great:

• Advanced knowledge of statistics and experience using statistical packages for analyzing datasets (Python, numpy, pandas, R, Excel, etc.)
• Excellent communication skills, both verbal and written
• BS in Mathematics, Economics, Computer Science, Information Management, Statistics or equivalent experience
• Intermediate to advanced knowledge of Python
• Expertise with Looker
• Experience with Data Build Tool (dbt)
• Experience with embedded analytics solutions

Brazil, Londrina

At Platform Science, we’re working to connect everything that moves.

Founded in 2015, we are an open IoT platform that partners with innovative fleets, application developers, vehicle manufacturers, and equipment providers in the transportation industry to deliver revolutionary solutions to supply chain professionals across the globe.

Our employees are an engaging, diverse group of people who believe in the power of great ideas. We hire people with different experiences and perspectives to build a company culture that fuels growth through innovation.

We value thoughtful actions and empathy for others. We approach challenges with resiliency and creativity, while encouraging transparency because, no matter our backgrounds or responsibilities, we are one team.cker, and Kubernetes.

What You’ll Do:

• Serve as a developer for our data analytics platform, informing technical direction, standards, and long-term strategy for data ingestion, storage, processing, and consumption.
• Partner with business stakeholders, product owners, engineers, analysts, and data scientists to design and develop highly scalable, resilient, and performant software and data architectures for both batch and streaming data pipelines.
• Collaborate closely with product and engineering teams to define and enforce governance around data models that enable complex analysis, visualization, and data science across the organization.
• Leverage our modern data stack (e.g., Snowflake/dbt), to continue to buildout, data model, cost optimize, and manage our data warehouse.
• Partner with Data Scientists to design, build, and productionize robust Machine Learning pipelines and feature stores.
• Establish data quality standards and processes to ensure data is properly filtered, cleaned, and transformed from a variety of sources to enable accurate and trustworthy analysis.
• Work directly with management and executive teams to prioritize and scope platform initiatives that align with the company's highest business and information needs.
• Mentor and coach team members on best practices, complex system design, and career growth, serving as an authoritative voice for data engineering excellence.

What We’re Looking For:

• 3+ years of progressive experience as a Data Engineer, focusing on building high-scale, production-grade data analytics platforms.
• Proficiency (3+ years) in software development, including the ability to write expert-level, maintainable, and robust code using Python and SQL.
• 3+ years designing, managing, and maintaining data warehouses (especially modern columnar databases), including expertise in dimensional data modeling and maintaining complex ETL/ELT pipelines.
• Experience working with both OLTP/OLAP relational databases and distributed data systems.
• 3+ years working with AWS services such as EC2, Lambda, S3, RDS, ECR, EKS, IAM, and IoT, specifically in the context of data infrastructure.
• 3+ years of experience working with streaming data technologies such as Kinesis, Kafka, or Storm, and designing real-time data processing architectures.
• Advanced SQL skills including performance tuning, window functions, and complex query optimization.

Great to have:

• Proven ability to design and manage CI/CD pipelines using tools like Jenkins, TravisCI, or GitLab Runners for data platform code deployment.
• Demonstrated experience using Terraform (or similar IaC tool like CloudFormation) to provision, manage, and scale cloud infrastructure, data pipelines, and platform resources.
• Hands-on experience with AWS Database Migration Service (DMS) for large-scale database migrations and continuous data replication from various data sources.
• Demonstrated technical leadership regarding all things data: mining, modeling, transformation, cleansing, validation, security, and governance.
• Exceptional communication and presentation skills, with the ability to articulate complex technical trade-offs to both technical and non-technical audiences.
• Experience building and managing a workflow management system such as Airflow, Luigi, or Prefect.
• Expertise with containerization and orchestration using Docker/Kubernetes/EKS.
• Proven experience building and optimizing serverless data pipelines (e.g., AWS Lambda, Step Functions).
• Experience with Data Build Tool (dbt) for transformation and modeling.
• Experience with Snowflake or other major columnar/cloud data warehouses.
• BS/MS in Computer Science, Engineering, or equivalent practical experience.
• Experience with Feature Store architectures (e.g., Feast, Tecton) and developing standardized feature engineering pipelines.

About the Team

At DoorDash, people are our most important asset. We build the capability to help our leaders make more informed decisions on identifying, attracting, developing, and retaining talent. We’re looking for a Data Engineer to help us scale our analytics alongside DoorDash’s enormous growth. Come build, experiment, and grow while shaping a best-in-class data team at DoorDash.

About the Role

DoorDash is seeking an experienced data engineer to join our People Intelligence team supporting HR functions. We’re a data-driven organization, empowering local economies and our people to do the best work of their careers. This role will get in on the ground floor helping to build and support the data infrastructure powering our data-driven insights to attract, develop, and retain the best talent to power and grow DoorDash. You will support and scale our people reporting and analytics within the People Team. In this role, you will partner with a team of analysts, scientists, and engineers to develop the tools and insights for our people and decision-makers. Come help us enable our business to garner insights and be a builder, engineer, consultant, and security/privacy advocate. 

You’re excited about this opportunity because you will…

• Architect and engineer our data infrastructure for People data
• Design and implement data warehouse schemas, tables, and views to provide a source of true datasets
• Develop ETL pipelines using tools such as Airflow and dbt for data profiling, cleaning, and transformation
• Support self-service analytics projects by creating secure data structures
• Provide underlying data support for all People metrics (recruiting pipelines, attrition, employee engagement, diversity and inclusion, compensation and benefits, etc.)
• Ensure data integrity across all People data
• Rigorously document system requirements and configuration to build operational excellence
• Understand and identify opportunities to improve, working closely with cross-functional teams
• Train peers on new processes and functionality as needed
• Help build data governance with a single source of truth

We’re excited about you because you have…

• 5+ years of industry experience in data engineering or software engineering
• Experience deploying cloud architecture like dbt, Airflow, and Databricks in AWS
• Expert SQL skills and experience writing complex queries
• Proficiency authoring Airflow DAGs
• Experience with data observability and monitoring frameworks
• Strong business thinker, able to use ‘first principles’ to solve challenging business problems at their root level
• Data-driven, able to analyze data with strong attention to detail and accuracy, and passionate about telling the story behind the data hence turning the data into insight

Notice to Applicants for Jobs Located in NYC or Remote Jobs Associated With Office in NYC Only

We use Covey as part of our hiring and/or promotional process for jobs in NYC and certain features may qualify it as an AEDT in NYC. As part of the hiring and/or promotion process, we provide Covey with job requirements and candidate submitted applications. We began using Covey Scout for Inbound from August 21, 2023, through December 21, 2023, and resumed using Covey Scout for Inbound again on June 29, 2024.

The Covey tool has been reviewed by an independent auditor. Results of the audit may be viewed here: Covey

Seeking to hire a Contractor based out of Mexico or Argentina for Lead Analytics Engineering Data Team

• We are looking for a Lead Analytics Engineer to join our data team.
• Reporting to the Hiring Manager, you will be responsible for applying data engineering best practices to analytics code to transform, test, and document data.
• You will provide clean and organized data sets to end users.
• You will be provide expert code reviews and mentorship to other engineers in the data space
• You will be responsible for building and maintaining composable data models, as well as optimizing SQL query performance for the models you build.
• You will transform raw data into business insights, working closely with stakeholders and developing analyses to answer critical business questions.
• You will create data visualizations and help stakeholders explore and understand the data visualization tools available to them.

Why you'll love this role:Data Modeling and Transformation

• Build new analyses and support existing ones using SQL and Python.
• Apply software engineering principles like version control and continuous integration to the analytics codebase.
• Expand our data warehouse with clean data ready for analysis.

Data Quality and Testing

• Apply advanced data testing strategies to ensure resulting datastores are aligned with expected business logic.
• Implement validation checks and automated testing procedures to manage data quality in your ETL/ELT pipelines.

Collaboration and Communication

• Work with stakeholders to define business logic and data expectations.
• Help drive a change in the usage of data by actively surfacing insights to stakeholders.
• Lead initiatives and problem definition, scoping, design, and planning.

Infrastructure and Automation

• Build tools and automation to run data infrastructure.
• Manage large-scale data migrations in relational datastores.

Why you're a great fit:

• 8+ Years experience working with data in a software environment. 
• Required Skills: Mastered proficiency in SQL and Python; advanced experience managing business semantic layer tooling, data catalog tooling and  data integrity testing frameworks. Experience with dbt orchestration and best practices.
• You have a track record of working autonomously and proactively, with deep domain knowledge of data systems.
• Required Tech Stack: SQL, Python, relational datastores, DAG tooling (like Dagster or Airflow), dbt and Tableau.
• Experience with cloud-based infrastructure (AWS, GCP, Terraform) and document, graph, or schema-less datastores.

Please note that given the nature of the contract, this role will not be eligible to participate in company-sponsored benefits

About Newsela:

Newsela is a leading education technology company dedicated to meaningful classroom learning for every student. We deliver integrated, AI-powered solutions designed to unlock student engagement, empower teachers, and drive meaningful learning outcomes. Our suite of products supports knowledge and skill development, writing practice, daily instruction, assessment, and data-informed decision-making across K–12 classrooms. Grounded in learning science research, Newsela’s solutions integrate content, assessment, and analytics to help educators track progress, understand student outcomes, and deliver high-impact instruction that supports every learner.

#LI-Remote

The salary range for this role is negotiable, the range being $6,000-$12,500 per month (Gross in USD), based on location and experience level.  

About Sezzle:

With a mission to financially empower the next generation, Sezzle is revolutionizing the shopping experience beyond payments, blending cutting-edge tech with seamless, interest-free installment plans that make shopping smarter and more accessible. We’re not just transforming payments; we’re redefining how people discover, interact with, and purchase the things they love while driving real impact on merchant sales through increased conversions and higher order values. As we continue to shape the future of fintech and retail, we’re building an innovative, dynamic team passionate about creating more than just a transaction but a truly unique shopping journey. If you’re excited about pushing boundaries in tech and delivering a game-changing experience for consumers and merchants alike, come join us at Sezzle and help create the future of shopping!

Compensation:

For this principal development role, with 12+ years of experience, the compensation range is  $6,000 - $12,500 USD based on location and experience level per month and in gross amount. This range acknowledges the extensive expertise, leadership capabilities, and significant contributions expected at this level, offering a competitive salary to reflect the value of advanced skills and experience

About the Role: 

We are seeking a talented and motivated, best-in-class Principal Engineer for our Data Infrastructure. This role presents an exciting opportunity to thrive in a dynamic, fast-paced environment within a rapidly growing team, with abundant prospects for career advancement.

Sezzle is growing; our data generation and consumption is growing with us at an increasing scale. Data is extremely valuable, and we want to empower the business, the engineers, and the rest of the organization to be able to read, write, and analyze large volumes of it quickly and efficiently.

Sezzle is a heavy consumer of MySQL, Postgres, and Redshift, leveraging AWS tooling with Aurora RDS and DMS. We use DBT-based transformations and similar toolkits to populate a rapidly growing data lake that supports multiple data warehouses. It’s scaled well with us so far, and we’re looking to continue improving it, but we also want to step into new tooling and technologies.

What you’ll do: 

• End to end ownership of our database and data warehousing infrastructure, its KPIs and its SLAs, including MySQL, Postgres, CDC capture, and Redshift.
• Lead optimizations in database and query performance.
• ​​Build and maintain tooling to help manage and upgrade our data infrastructure, continually improving with migrations and optimizations.
• Partner with Development to ensure we ship solid queries against a battle-tested schema to meet the needs of our products and business.

• Help Sezzle evolve our data systems beyond the current scale and stack with whatever tooling is necessary to handle processing high volumes of writes and events while performing complex ETL.
• Evaluate and integrate new technologies, guiding the evolution of Sezzle’s data infrastructure.
• Help data engineers and analysts optimize Redshift and warehouse performance, including query tuning, modeling improvements, and cost management.

What We look for: 

• 12+ years of experience in DBA, SRE, or Data Engineering roles, with a strong track record of scaling production-grade systems.
• Deep expertise with MySQL, Postgres, AWS Redshift or similar products, including performance tuning, table design, and workload management.
• Advanced proficiency in SQL.
• Strong hands-on experience with data replication and ETL/ELT frameworks, especially DBT, AWS DMS, or similar tools.
• Strong understanding of data modeling, distributed systems, and warehouse/lake design patterns.
• Ability to work in a fast-paced, collaborative environment with excellent communication and documentation skills.

Preferred Knowledge and Skills:

• Prior experience in high-growth, data-intensive fintech or similar regulated environments.
• Knowledge of lakehouse architectures and modern stacks such as Snowflake, Databricks, Iceberg, or Delta Lake.
• Some background in designing scalable, fault-tolerant data pipelines using modern orchestration tools (Airflow, Dagster, Prefect, etc.) processing anywhere from 100GB to 1 TB of new data a day
• Familiarity with streaming technologies (Kafka, Kinesis, Flink, Spark Streaming).
• High enthusiasm for using AI to be as productive as possible.

About You: 

• You have relentlessly high standards - many people may think your standards are unreasonably high. You are continually raising the bar and driving those around you to deliver great results. You make sure that defects do not get sent down the line and that problems are fixed so they stay fixed.
• You’re not bound by convention - your success—and much of the fun—lies in developing new ways to do things
• You need action - speed matters in business. Many decisions and actions are reversible and do not need extensive study. We value calculated risk-taking.
• You earn trust - you listen attentively, speak candidly, and treat others respectfully.
• You have backbone; disagree, then commit - you can respectfully challenge decisions when you disagree, even when doing so is uncomfortable or exhausting. You have conviction and are tenacious. You do not compromise for the sake of social cohesion. Once a decision is determined, you commit wholly.
• You deliver results - you focus on the key inputs and deliver them with the right quality and in a timely fashion. Despite setbacks, you rise to the occasion and never settle.

Sezzle’s Technology Stack:

• Languages: Golang, Typescript, Python
• Frontend: Typescript - React and React Native
• Backend: Golang
• Database: MySQL, Postgres, Elasticsearch
• DevOps & Cloud: AWS, Kubernetes
• Version Control: Git
• CI/CD: Gitlab
• Testing: Developer and AI-driven, focus on automated end-to-end, integration, and unit tests
• Open Source: Sezzle is focused on using open source, and we build what we can before buying!

What Makes Working at Sezzle Awesome? 

At Sezzle, we are more than just brilliant engineers, passionate data enthusiasts, out-of-the-box thinkers, and determined innovators; we are skilled musicians, yogis, cyclists, chefs, golfers, dog-lovers, and rock-climbers. We believe in surrounding ourselves with not only the best and the brightest individuals, but those that are unique and purpose-driven in all that they do. Our culture is not defined by a certain set of perks designed to give the illusion of the traditional startup culture, but rather, it is the visible example living in every employee that we hire.

#Li-remote #full-time

The Role You’ll Play: 

As a Staff Software Engineer for the Data Platform Engineer team, you’ll shape the backbone of our data strategy—designing scalable pipelines, championing governance, and enabling AI-ready infrastructure. You’ll lead cross-functional projects that fuel analytics, automation, and decision-making across the Playlist ecosystem. Your work will directly empower our teams to create personalized, real-world experiences for millions of users.

• Architect and optimize cloud-native data warehouse solutions that power real-time decisions and long-term strategy
• Design and scale dbt models across bronze/silver layers with a focus on data contracts, observability, and semantic consistency
• Build and maintain robust ETL/ELT pipelines using tools like Fivetran, Snowpipe, and CDC to support streaming and batch workloads
• Lead the design of infrastructure-as-code deployments with Pulumi or Terraform, driving CI/CD maturity and cost-efficient operations
• Elevate data quality with comprehensive monitoring, anomaly detection, and validation frameworks
• Collaborate across squads to align data contracts, expand shared data marts, and support machine learning enablement
• Champion data governance, ensuring privacy and compliance through PII tagging, lineage, and role-based access controls
• Drive continuous platform improvement through systematic tech debt remediation and modernization initiatives

Experience You Bring:  

• Strong expertise in data engineering, software engineering, platform architecture, or modern data warehousing
• Proficient in Python and SQL for automation, transformation logic, and data platform development
• Experience implementing observability standards, anomaly detection, and data quality validation
• Proven ability to lead complex, multi-squad initiatives and deliver scalable outcomes
• Hands-on experience with job orchestration and infrastructure as code (e.g., Pulumi, Terraform)
• Strong understanding of data modeling principles and architectural patterns such as star schemas and bronze/silver/gold layering
• Comfort mentoring engineers, influencing technical roadmaps, and advocating for best practices

Why Valtech? We’re the experience innovation company - a trusted partner to the world’s most recognized brands. To our people we offer growth opportunities, a values-driven culture, international careers and the chance to shape the future of experience. 

The opportunity

At Valtech, you’ll find an environment designed for continuous learning, meaningful impact, and professional growth. Whether you're pioneering new digital solutions, challenging conventional thinking or building the next generation of customer experiences, your work will help transform industries. 

We are proud of: 

• The work we do and the innovation we drive 
• Our values of share, care and dare 
• A workplace culture that fosters creativity, diversity and autonomy 
• Our borderless, global framework, which enables seamless collaboration 

The role  

We are seeking a Senior Data Engineer with a strong background in data engineering, ideally with hands-on experience in Google Cloud Platform (GCP) services such as Pub/Sub, Dataflow, and BigQuery. The ideal candidate will have solid proficiency in SQL and Python, along with familiarity in moving and transforming data across cloud-based data zones and streaming pipelines (ETL/ELT). Comfort with cloud services, data management, automation tools, and real-time data processing is essential. 

Role responsibilities

• Demonstrate deep knowledge of the data engineering domain to build and support non-interactive (batch, distributed) & real-time, highly available data pipelines  
• Build fault-tolerant, self-healing, adaptive, and highly accurate data computational pipelines  
• Provide consultation and lead the implementation of complex programs  
• Develop and maintain documentation relating to all assigned systems and projects  
• Tune queries running over billions of rows of data running in a distributed query engine  
• Perform root cause analysis to identify permanent resolutions to software or business process issues
• Implement and maintain dbt transformation models, CI pipelines, and data contracts for curated campaign, ad group, keyword, audience, and landing-page marts.
• Build and monitor data quality gates (Great Expectations and reconciliation checks) and freshness SLOs.
• Optimize BigQuery cost and performance using query tuning, storage design, and reservation strategy.
• Implement platform hardening controls including retries, dead-letter queues, DR runbooks, and support for VPC-SC and DLP validation.

Must have qualifications

To be considered for this role, you must meet the following essential qualifications: 

• Strong expertise in:   
  • Python - for building data pipelines, processing tasks, and automation  
  • SQL - Advanced SQL capabilities (nested fields, analytic functions).  
• Hands-on experience with Core GCP Data Stack:  
  • BigQuery: Expert-level SQL, performance tuning, and specifically BigQuery for advanced SQL, performance tuning, partitioning and clustering strategy, and production-grade curated marts and feature tables; working knowledge of BQML for scoring and evaluation in analytics workflows. 
  • Dataflow (Apache Beam)
  • Strong proficiency in building reliable batch and incremental pipelines for GA4/Google Ads data into BigQuery, with streaming patterns (windowing/watermarks/triggers) used when near-real-time alerting is required.
  • Pub/Sub: Experience with event-driven architecture and message queuing.  
• Hands-on experience with Visualization & BI:       
  
  • Looker Core – Advanced proficiency in LookML (not just drag-and-drop), including derived tables, explores, and Liquid syntax.  
  • Semantic Modeling: Develop robust LookML models to create a trusted layer of data governance, ensuring metrics are consistent across the organization.  
  • Dashboard Creation: Design intuitive, high-impact dashboards in Looker for two distinct audiences: Operational teams (paid search performance monitoring, anomaly triage, and optimization workflows) and Executives (ROAS, conversion efficiency, budget pacing, and channel contribution reporting). 
• Ability to independently own workstreams while collaborating closely with data science, analytics, and engineering peers in agile delivery.
• Advanced English skills 

Nice to have qualifications  

• Google Cloud Professional Data Engineer certification  
• Google Professional Machine Learning Engineer certification  
• Google Cloud Professional Cloud Architect certification  
• Bachelor’s or Master’s degree in a quantitative or technical field (e.g., Computer Science, Engineering, Statistics)    
• Working knowledge of cloud architecture components in GCP  
• Proficiency in Big Data environments and tools such as Spark, Hive, Impala, Pig, etc.  
• Proficiency in Terraform  
• Familiarity with front and back-end web application stacks and frameworks, and API design and usage (REST/GraphQL)    
• Experience leading and managing technical data/analytics/machine learning projects    
• Experience supporting data products consumed by conversational analytics surfaces (BigQuery/Looker query routing, audit logging, and row-level access patterns).

If you do not meet all the listed qualifications or have gaps in your experience, we still encourage you to apply. At Valtech, we recognize that talent comes in many forms, and we value diverse perspectives and a willingness to learn. 

Commitment to reaching all kinds of people 

We design experiences that work for all kinds of people - and that starts with our own teams. At Valtech, we’re intentional about building an inclusive culture where everyone feels supported to grow, thrive and achieve their goals. No matter your background, you belong here. Explore our Diversity & Inclusion site to see how we’re creating a more equitable Valtech for all. 

Your application process

Once you apply, our Talent Acquisition team will review your application. If your skills and experience align with the role, we’ll reach out for next steps. Your CV should cover key information on relevant experiences and expertise. We do not require information such as age, gender, marital status, or a headshot in your application. We review all candidates based on skills, experience, and potential.

⚠️ Beware of recruitment fraud: Only engage with official Valtech email addresses.

We are committed to inclusion and accessibility. If you need reasonable accommodations during the interview process, please either indicate it in your application or let your Talent Partner know. 

About Valtech

Valtech is the experience innovation company that exists to unlock a better way to experience the world. By blending crafts, categories, and cultures, we help brands unlock new value in an increasingly digital world. 

At the intersection of data, AI, creativity, and technology, we drive transformation for leading organizations, including L’Oréal, Mars, Audi, P&G, Volkswagen Dolby, and more. 

At Valtech, we don’t just talk about transformation. We make it happen. Our people are the heart of our success, and we foster a workplace where everyone has the support to thrive, grow and innovate. 

Are you ready to create what’s next? Join us.

Important Information 

Location: Brazil
Job Mode: Full-time 
Work Mode: Work from home

Job Summary

We are seeking a highly experienced Data Engineer Lead to architect, develop, and deliver robust, scalable, end-to-end automation solutions. This role demands deep technical expertise across solution architecture, environment setup, deployments, observability, governance, and continuous improvement. The ideal candidate is a strong technical leader and communicator who partners closely with business stakeholders to define automation strategies and deliver high-impact, enterprise-grade solutions.

Responsibilities and Duties

• Lead and mentor a team of data engineers, providing technical guidance, code reviews, and best practices to ensure high-quality deliverables;
• Own the end-to-end data migration strategy from Snowflake on AWS to Azure Databricks and DBT, including planning, execution, and optimization;
• Collaborate with cross-functional stakeholders (data, product, architecture, and business teams) to align data initiatives with organizational goals;
• Architect and oversee scalable, secure, and reliable data pipelines and infrastructure in Azure;
• Drive the design and implementation of infrastructure-as-code using Terraform, ensuring consistency and maintainability;
• Ensure efficient data integration between Snowflake and Azure environments, establishing robust and scalable data flows;
• Oversee data transformation frameworks using Databricks and DBT, promoting reusable and modular design patterns;
• Establish and enforce data engineering standards, governance practices, and CI/CD workflows;
• Proactively identify risks, troubleshoot complex technical issues, and implement long-term solutions;
• Lead documentation efforts for architecture, processes, and best practices across the data platform.

Essential Skills

• Experience in Data Engineering;
• Proven experience leading data engineering teams and delivering large-scale data platform initiatives;
• Strong hands-on experience with Snowflake, Azure Databricks, and DBT;
• Deep expertise in cloud infrastructure and infrastructure-as-code tools, especially Terraform;
• Extensive experience with cloud data migration projects (AWS to Azure preferred);
• Strong experience with CI/CD pipelines and Git-based version control;
• Advanced proficiency in SQL, data modeling, and ETL/ELT design patterns;
• Strong understanding of data architecture, scalability, and performance optimization;
• Ability to operate in a fast-paced, collaborative, and evolving environment;
• Mandatory experience in the insurance industry, with understanding of insurance data domains (policies, claims, underwriting, etc.).

Highly Desirable Skills

• Experience with data governance frameworks (data cataloging, lineage, quality, and observability tools);
• Knowledge of security and compliance standards relevant to insurance and financial data;
• Familiarity with streaming and real-time data processing (Kafka, Event Hubs, Delta Live Tables);
• Experience designing lakehouse architectures and implementing cost-optimization strategies;
• Exposure to multi-cloud environments and advanced automation practices.

About Encora

Encora is the preferred digital engineering and modernization partner of some of the world’s leading enterprises and digital native companies. With over 9,000 experts in 47+ offices and innovation labs worldwide, Encora’s technology practices include Product Engineering & Development, Cloud Services, Quality Engineering, DevSecOps, Data & Analytics, Digital Experience, Cybersecurity, and AI & LLM Engineering.

At Encora, we hire professionals based solely on their skills and qualifications, and do not discriminate based on age, disability, religion, gender, sexual orientation, socioeconomic status, or nationality.

Important Information 

Location: Brazil
Job Mode: Full-time 
Work Mode: Work from home

Job Summary

We are seeking a highly experienced Software Development Engineer in Test (19742) with a strong background in data quality, analytics testing, and data engineering validation within the insurance industry. This role focuses on ensuring high-quality data across modern data platforms by defining, implementing, and maintaining robust testing strategies across the full data lifecycle—from raw ingestion to curated analytical layers. The ideal candidate demonstrates technical leadership, continuous improvement, and strong collaboration with engineering and business stakeholders.

Responsibilities and Duties

• Develop and maintain end-to-end dbt testing frameworks, including mocked and expected datasets across bronze, silver, and gold layers;
• Define, implement, and maintain dbt models, unit tests, end-to-end tests, and custom test cases;
• Analyze engineering and analytics requirements to determine appropriate testing scope and strategies;
• Collaborate closely with business stakeholders, Data Engineers (DEs), and Analytics Engineers (AEs) to define testing needs and ensure data quality alignment;
• Gain a deep understanding of the repositories, tools, and workflows, including VSCode, pytest, dbt, Databricks, Git, Docker, and CI/CD processes;
• Investigate failed tests, perform root cause analysis, and support defect resolution;
• Review pull requests to ensure adherence to testing standards and data quality best practices;
• Actively participate in Agile ceremonies, providing quality insights and recommendations;
• Identify opportunities for process optimization, automation, and efficiency improvements while aligning quality efforts to business value;
• Demonstrate leadership by mentoring team members and promoting best practices in Quality Engineering.

Essential Skills

• Experience in Quality Engineering, with a strong focus on data-centric testing;
• Proven experience working within the insurance industry (required);
• Strong understanding of data warehousing concepts, ETL processes, and BI platforms;
• Solid knowledge of testing strategies, the Test Pyramid, and version control systems;
• Proficiency in SQL and scripting languages such as Python;
• Demonstrated ability to drive continuous improvement across technology, processes, and people.

Highly Desirable Skills

• Hands-on experience designing and executing data validation strategies across complex data pipelines;
• Ability to translate business and analytical requirements into effective testing solutions;
• Experience supporting enterprise-scale data platforms with a strong emphasis on data accuracy, reliability, and compliance;
• Comfortable working in fast-paced, Agile environments.

About Encora

Encora is the preferred digital engineering and modernization partner of some of the world’s leading enterprises and digital native companies. With over 9,000 experts in 47+ offices and innovation labs worldwide, Encora’s technology practices include Product Engineering & Development, Cloud Services, Quality Engineering, DevSecOps, Data & Analytics, Digital Experience, Cybersecurity, and AI & LLM Engineering.

At Encora, we hire professionals based solely on their skills and qualifications, and do not discriminate based on age, disability, religion, gender, sexual orientation, socioeconomic status, or nationality.

Data at Brex

The Data organization develops insights, models, and data infrastructure for teams across Brex, including Sales, Marketing, Product, Engineering, and Operations. Our Data Scientists, Analysts, and Engineers work together to make data—and insights derived from data—a core asset across the company.

What you’ll do

As a Data Analyst II (DA), you will play a central role in enhancing the operational tracking and reporting capabilities of different business teams across Brex. You will work closely with Data Scientists, Data Engineers, and partner teams to drive meaningful insights for the business through visualizations, self-service tools, and ad-hoc analyses. This is a high-impact role in a fast-paced fintech environment where your work will directly influence strategic decisions.

Where you’ll work

This role will be based in our São Paulo office. We are a hybrid environment that combines the energy and connections of being in the office with the benefits and flexibility of working from home. We currently require a minimum of three coordinated days in the office per week, Monday, Wednesday and Thursday. As a perk, we also have up to four weeks per year of fully remote work!

Responsibilities

• Apply data visualization and storytelling skills in creating business intelligence solutions (such as Looker and/or Hex dashboards) that enable actionable insights.
• Perform ad-hoc analyses and deep dives to investigate business questions, surface trends, and provide data-driven recommendations.
• Develop self-service data tools and processes that empower business stakeholders to independently monitor the performance and health of their respective areas.
• Collaborate closely with Data Scientists and Data Engineers to identify data sources, enable data pipelines, and support the development of analytical data models that operationalize reports and dashboards.
• Implement and maintain rigorous data quality checks to ensure the integrity and robustness of datasets used across dashboards, reports, and analyses.
• Partner with various departments—including Sales, Operations, Product, and Finance—to understand their data needs and deliver tailored analyses and reporting that support strategic planning.
• Contribute to the automation of recurring analyses and reporting workflows using Python.

Requirements

• 4+ years of experience in data analytics or a related role in a professional setting.
• 3+ years of experience working directly with Sales, Operations, Product, or equivalent business teams.
• Fluency in SQL to manipulate data and perform complex analyses (CTEs, window functions, joins across large datasets).
• Proficiency in Python for data analysis, automation, and scripting (Pandas, NumPy, and similar libraries).
• Experience with business intelligence and data visualization tools (Looker, Hex, Tableau, or similar).
• Strong quantitative and analytical skills with a demonstrated ability to translate data into business insights.
• Strong communication skills and the ability to work effectively with stakeholders across different functions and levels of technical fluency.
• Experience with generative AI and LLM-based tools (Claude Code, Cursor, GitHub Copilot) to perform and accelerate analyses, automated reporting, and build self-service data tools.

Bonus points

• Familiarity with cloud data platforms (e.g., Snowflake, BigQuery, Databricks).
• Familiarity with dbt for data modeling and transformation.
• Exposure to data pipeline orchestration tools (e.g., Airflow).
• Experience in fintech, financial services, or payments.
• Comfort operating in a fast-paced, high-growth environment with evolving priorities.

Brex LLC is a wholly owned subsidiary of Capital One, N.A.

The Role

The Data Practice Director is a senior leadership role within Caylent's Cloud Data Engineering (CDE) practice, reporting directly to the Data Practice Leader. This person is responsible for operationalizing the practice strategy, leading a team of data professionals, and owning delivery excellence across a portfolio of client engagements. They are the connective tissue between strategic direction and day-to-day execution, ensuring the practice delivers consistent, high-quality outcomes while scaling to meet growth targets.

Your Assignment

Practice Operations and Delivery

• Own end-to-end delivery oversight for a portfolio of data engineering and analytics engagements, ensuring on-time, on-budget, and high-quality outcomes.
• Drive operational rigor across the practice including utilization management, staffing coordination, margin tracking, and engagement health reviews.
• Develop and enforce delivery standards, reusable frameworks, and best practices that enable consistent, scalable execution across the team.
• Serve as an escalation point for active engagements, helping resolve technical blockers, scope issues, and client concerns in partnership with delivery leads.
• Partner with the Practice Leader to translate the strategic roadmap into executable quarterly priorities and team-level OKRs.

Team Leadership and Development

• Directly lead and develop a team of data engineers, architects, and analytics professionals across the practice.
• Set clear performance expectations, conduct regular reviews, and provide ongoing coaching to build a high-performing, engaged team.
• Partner with recruiting and workforce planning to identify talent gaps, support hiring decisions, and onboard new team members effectively.
• Foster a culture of ownership, continuous learning, and technical excellence across a globally distributed team.
• Identify and develop emerging leaders within the practice, creating growth pathways aligned to practice needs.

Client Engagement

• Build trusted advisor relationships with key client stakeholders, acting as a senior point of contact for delivery and strategic guidance.
• Partner with the sales and GTM teams to support business development activities including scoping, proposal development, and technical solutioning for new and existing accounts.
• Identify and pursue expansion opportunities within active client engagements, surfacing new use cases and service offerings that align with client needs.
• Represent Caylent with credibility and professionalism in client-facing conversations at the director and VP level.

Practice Growth and Enablement

• Collaborate with the Practice Leader on go-to-market positioning, service offering development, and internal capability building.
• Contribute to thought leadership content including whitepapers, webinars, and conference presentations that elevate the practice's external profile.
• Stay current on trends in the modern data ecosystem and work with the team to incorporate relevant innovations into our delivery approach.
• Support the development of practice IP including accelerators, reference architectures, and reusable solution components.

Your Qualifications

Experience

• 12+ years of experience in professional services or consulting, with a strong focus on data engineering, analytics, or data platform delivery.
• Demonstrated success managing and growing a team of 20 or more data professionals in a services or consulting environment.
• Proven track record of delivering complex data projects on AWS, including data lake, lakehouse, streaming, and analytics workloads.
• Experience managing a portfolio of concurrent client engagements, balancing delivery quality with financial performance.
• Hands-on background in data architecture or engineering, with the ability to engage credibly with technical teams and client stakeholders alike.

Leadership

• Strong people management skills with demonstrated ability to develop talent, drive performance, and build team culture across geographies.
• Ability to operate effectively at multiple levels, from strategic planning conversations with the Practice Leader to hands-on engagement support with delivery teams.
• Comfortable navigating ambiguity and complexity in a fast-paced, high-growth consulting environment.
• Experience influencing senior client stakeholders (director, VP and C-level) in delivery and advisory contexts.

Technical Acumen

• Deep familiarity with the AWS data ecosystem including services such as Redshift, Glue, EMR, Kinesis, Lake Formation, and Athena.
• Working knowledge of adjacent platforms including Databricks and Snowflake, and their integration with AWS-native architectures.
• Broad understanding of data engineering fundamentals: ingestion patterns, transformation frameworks (e.g., Spark, dbt), data modeling, governance, and quality management.
• Familiarity with MLOps and data science workflows sufficient to support and position those capabilities in client conversations.

Education

• Bachelor's degree in Computer Science, Data Science, Information Systems, or a related field.
• Master's degree or MBA is a plus.

Certifications

• AWS Certified Data Analytics, AWS Certified Solutions Architect, or equivalent certifications are a plus.

Preferred Qualifications

• Execution-Oriented: Skilled at translating strategy into structured plans and holding teams accountable to outcomes.
• Client-First Mindset: Genuinely invested in client success and capable of building durable, trust-based relationships.
• Collaborative Partner: Works effectively across sales, delivery, and practice leadership functions without siloed thinking.
• Clear Communicator: Able to convey complex technical and business concepts to diverse audiences with clarity and confidence.
• Growth Driver: Passionate about building teams, capabilities, and client relationships that compound over time.

Benefits

• 100% remote work
• Generous holidays and flexible PTO
• Competitive phantom equity
• Paid for exams and certifications
• Peer bonus awards
• State of the art laptop and tools
• Equipment & Office Stipend
• Individual professional development plan
• Annual stipend for Learning and Development
• Work with an amazing worldwide team and in an incredible corporate culture

Key Responsibilities

• Build scalable, maintainable software solutions across the entire stack
• Develop using AI augmented workflows. Our engineers use Claude Code as their primary development tool with MCP connections to production data, Jira, Notion, Sentry, and Datadog. We expect engineers to actively leverage and improve these workflows.
• Diagnose bugs and address root causes to enhance stability; participate in on call rotations
• Actively engage in code reviews and technical discussions
• Systematically identify and mitigate technical debt
• Stay current with emerging technologies and participate in learning opportunities

Core Requirements

• 3+ years as a developer working with modern web frameworks (Rails, Django, or similar)
• Experience with front end technologies (React, Angular, TypeScript)
• Full stack development capability
• Ability to work effectively in geographically distributed, agile environments
• Active daily use of AI coding tools (Claude Code, Cursor, or similar) with demonstrated productivity gains. We are looking for engineers who have integrated AI into their development workflow, not just experimented with it.

Preferred Qualifications

• Specific expertise in Ruby on Rails, React, and React Native
• Experience building reusable AI workflows, skills, or tooling that others can use
• Computer Science degree (B.Sc. or higher)
• Infrastructure as code experience (AWS CDK, Terraform)
• Data platform experience (Snowflake, Fivetran, dbt)
• Early stage startup background

Compensation Ranges:

Range: $65,000–$80,000 USD

Leveling & Location:

Thanx uses structured internal levelling and location-based compensation. Final levelling and compensation are determined through the interview process based on experience, scope, and work location, and any offer will align to the appropriate range.

Application Process:

• This position is an existing vacancy.
• We may use artificial intelligence (AI) tools to assist in screening or assessing applications; human review will always remain part of the process.

Ready to change your life? Apply now!

We are proud to be an Equal Employment Opportunity company. We do not discriminate based on race, religion, color, national origin, gender (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics. Thanx will consider qualified applicants with arrest or conviction records for employment in a manner consistent with local requirements.

Key Responsibilities

• Build scalable, maintainable software solutions across the entire stack
• Develop using AI augmented workflows. Our engineers use Claude Code as their primary development tool with MCP connections to production data, Jira, Notion, Sentry, and Datadog. We expect engineers to actively leverage and improve these workflows.
• Diagnose bugs and address root causes to enhance stability; participate in on call rotations
• Actively engage in code reviews and technical discussions
• Systematically identify and mitigate technical debt
• Stay current with emerging technologies and participate in learning opportunities

Core Requirements

• 6+ years developing with modern web frameworks (Ruby on Rails, Django, or similar)
• Experience with front end technologies: React, Angular, TypeScript, or comparable tools
• Full stack capability with potential specialization in one area
• Strong communication skills for remote collaboration and cross functional discussions
• Active daily use of AI coding tools (Claude Code, Cursor, or similar) with demonstrated productivity gains. We are looking for engineers who have integrated AI into their development workflow, not just experimented with it.

Preferred Qualifications

• Specific expertise in Ruby on Rails, React, and React Native
• Experience building reusable AI workflows, skills, or tooling that others can use
• Computer Science degree (B.Sc. or higher)
• Infrastructure as code experience (AWS CDK, Terraform)
• Data platform experience (Snowflake, Fivetran, dbt)
• Early stage startup background

Compensation Ranges:
L4 Range: $75,000–$95,000 USD
L5 Range: $90,000–$110,000 USD

Leveling & Location:

Thanx uses structured internal levelling and location-based compensation. Final levelling and compensation are determined through the interview process based on experience, scope, and work location, and any offer will align to the appropriate range.

Application Process:

• This position is an existing vacancy.
• We may use artificial intelligence (AI) tools to assist in screening or assessing applications; human review will always remain part of the process.

Ready to change your life? Apply now!

We are proud to be an Equal Employment Opportunity company. We do not discriminate based on race, religion, color, national origin, gender (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics. Thanx will consider qualified applicants with arrest or conviction records for employment in a manner consistent with local requirements.

Somos o acelerador que impulsiona o crescimento na Ibero-América, combinando a excelência global em engenharia da EPAM com a experiência regional e a proximidade cultural da NEORIS. Ajudamos as organizações a escalar, modernizar e avançar em sua transformação digital por meio de soluções em Cloud, Data & Analytics, Inteligência Artificial, Cibersegurança, Automação Inteligente, Consultoria Estratégica e Engenharia de Software.

Respaldados por mais de 60.000 profissionais em mais de 55 países e por um sólido modelo Nearshore, conectamos capacidades globais com confiança local para gerar impacto real, crescimento sustentável e resultados de alto valor para nossos clientes.

Acreditamos que a diversidade impulsiona a inovação. Por isso, todas as nossas oportunidades estão abertas para todas as pessoas, independente de gênero, raça, idade, identidade, orientação ou condição. 

Oferecemos

• Vale Refeição e Vale Alimentação: Benefícios mensais para suas despesas com alimentação, dentro e fora de casa. 
• Previdência Privada: Planejamento de futuro com contribuição complementar à aposentadoria. 
• Plano de Saúde: Cobertura médica de alta qualidade para você e seu dependente legal. 
• Plano Odontológico: Cuidados odontológicos completos, com ampla rede de atendimento. 
• Seguro de Vida: Proteção e segurança para você e seus entes queridos. 
• Aulas de Inglês/Espanhol: Incentivo ao aprendizado de idiomas. 
• Wellhub: Benefícios e descontos em academias e programas de bem-estar. 
• Auxílio Creche: Suporte financeiro para despesas com educação infantil. 
• Neoris Global Campus: Plataforma de desenvolvimento com oportunidades contínuas de aprendizado e crescimento profissional. 
•  

Se você possui experiência e tem interesse em participar de iniciativas estratégicas, cadastre seu perfil em nosso banco de talentos.

Te convidamos a nos conhecer em http://www.neoris.com, Facebook, LinkedIn, Twitter e Instagram: @NEORIS.
#LI-KC1

• You will ensure new customers have an excellent experience by providing technical assistance early in their journey
• You will become an expert on the Databricks Platform and guide customers in making the best technical decisions
• You will work directly with multiple customers concurrently to provide technical solutions.

• Undergraduate degree or higher in Computer Science, Information Systems, or relevant experience
• 3+ years experience in a customer-facing technical role in pre-sales, professional services, consulting or customer success.
• Experience in one or more of the following:
• Solid understanding of the end to end data analytics workflow
• Excellent time management and prioritization skills
• Knowledge of public cloud platforms AWS, Azure or GCP would be a plus
• Knowledge of a programming language - Python, Scala, or SQL
• Knowledge of end-to-end data analytics workflow
• Hands-on professional or academic experience in one or more of the following:
• Data Engineering technologies (e.g., ETL, DBT, Spark, Airflow)
• Data Warehousing technologies (e.g., SQL, Stored Procedures, Redshift, Snowflake)
• Excellent time management and prioritization skills
• Excellent written and verbal communication, in English and Portuguese
• Bonus
  • Knowledge of Data Science and Machine Learning (e.g., build and deploy ML Models).
  • Databricks certification(s)

Why this Role Exists

At Blip, data doesn't just inform decisions—it powers experiences. But data at scale demands discipline: governance that enables (not blocks), costs that are predictable, and standards that accelerate (not slow down) teams.

We're migrating from Azure/Databricks to Google Cloud Platform with a clear mandate: build it right from day one. No legacy debt. No ungoverned pipelines. No cost surprises.

We're looking for a Staff Data Engineer with a rare blend: deep hands-on technical skills in data platforms plus strategic thinking in governance, cost optimization, and enablement. Someone who can turn policies into code, transform Google PSO artifacts into reusable templates, and scale best practices across domains—without becoming the "policy police."

Your Mission

You'll be the technical backbone of our Data & Analytics Center of Excellence (CoE), translating governance strategy into automation, patterns, and tooling that make "doing the right thing" the fastest and easiest path for data teams.

You'll work hand-in-hand with our Data Architect and Google Cloud Professional Services to:

• Implement governance-as-code
• Embed FinOps discipline into every pipeline, dataset, and model from day one.
• Build reusable templates, accelerators, and frameworks that scale across domains 
• Enable federated governance: empowering  teams with self-service tooling, guardrails, and observability.

Key Responsibilities

Governance Engineering & Automation

• Design and implement governance-as-code frameworks using GCP-native tools
• Build automated workflows for data classification, lineage tracking, quality validation, and compliance reporting (LGPD, GDPR, ISO 27001).
• Create reusable Infrastructure-as-Code (IaC) modules (Terraform) for governance foundations: project structure, IAM roles, security policies, audit logging, retention policies.
• Implement the Governance Seal framework: automated validation that datasets/pipelines meet minimum standards (quality, security, documentation, cost efficiency) before entering production.

FinOps for Data & Cost Optimization

• Embed FinOps best practices into CoE templates: partitioning strategies, clustering, storage classes (Standard/Nearline/Coldline/Archive), lifecycle policies, query optimization, slot reservations, autoscaling.
• Build cost monitoring and alerting for GCP data services.
• Identify, remediate and direct cost waste: unused tables, redundant pipelines, inefficient queries, over-provisioned resources.

CoE Platforms, Templates & Accelerators

• Transform deliverables (TDDs, IaC modules, pipeline patterns, KT sessions) into production-ready CoE standards: documented, versioned, tested, and reusable.
• Build a catalog of pipeline patterns and templates for common use cases: batch ingestion (JDBC, APIs, files), streaming (Pub/Sub, Kafka), CDC, data contracts, gold layer serving (fast + analytical).
• Develop self-service toolkits for Data Stewards and domain engineers: project setup scripts, data contract generators, quality rule templates, lineage visualization, metadata enrichment.
• Establish CI/CD patterns for data pipelines: automated testing (schema validation, data quality, security checks), deployment gates (Governance Seal validation), rollback strategies.

Data Modeling & Storage Design (Governance Lens)

• Design reference data models that embed governance from the start: clear ownership, semantic definitions, access policies, retention rules, lineage traceability.
• Optimize storage and compute for both performance and cost: partitioning, clustering, indexing, compression (Parquet, Avro), Delta/Iceberg table formats.
• Define standards for data contracts (schemas, SLAs, ownership, change management) and implement them as code (Avro schemas, Protobuf, dbt contracts, data validation frameworks).

Observability, Quality & Reliability

• Build data quality checks 
• Implement end-to-end data lineage (Dataplex, OpenLineage, custom metadata extraction) from source systems to analytics/AI consumption.
• Build monitoring and alerting for governance KPIs: policy compliance, data freshness, quality SLA breaches, access anomalies, cost overruns.
• Define and enforce SLAs/SLOs for data delivery, accuracy, and availability—across raw, trusted, and gold layers.

Enablement & Leadership

• Act as technical mentor and sparring partner for Data Stewards, domain engineers, and analytics teams adopting CoE standards.
• Lead design reviews and architecture spikes for governance, FinOps, and platform patterns.
• Produce playbooks, runbooks, and hands-on labs: "How to set up a governed project in GCP," "FinOps checklist for BigQuery," "Implementing dynamic data masking," etc.
• Facilitate Community of Practice sessions: share patterns, troubleshoot blockers, celebrate wins, iterate on feedback.

What We’re Looking For

Experience

• 6+ years in Data Engineering, Platform Engineering, or Data Infrastructure roles, with at least 2 years focused on governance, data quality, or platform enablement.
• Proven experience implementing data governance frameworks in production: metadata management, access control, data quality, lineage, compliance.
• Hands-on experience with FinOps for data platforms: cost monitoring, optimization, chargeback/showback models, budgeting.
• Experience building reusable frameworks, templates, or internal platforms that other engineers consume (not just one-off pipelines).

Technical Foundations

• GCP expertise (required): BigQuery (IAM, policies, partitioning, clustering, masking), Dataplex (lakes, zones, catalog, lineage, quality), Cloud Storage, Pub/Sub, Dataproc, Composer/Airflow, Cloud DLP, IAM.
• Infrastructure-as-Code: Terraform (or equivalent) for provisioning and managing GCP data infrastructure at scale.
• Programming: Strong Python and SQL; ability to write clean, testable, maintainable code for data pipelines and automation.
• Data modeling: Deep understanding of dimensional modeling, event sourcing, CDC, slowly changing dimensions, data contracts, schema evolution.
• CI/CD for data: Experience with automated testing, deployment pipelines, version control (Git), and release management for data products.
• Data quality & observability tools: Great Expectations, dbt, Dataplex Data Quality, OpenLineage, or similar.

Governance & Compliance Knowledge

• • Understanding of data privacy regulations (LGPD, GDPR) and how to implement technical controls: data classification, masking, anonymization, retention, audit trails.
  • Experience with Data Loss Prevention (DLP) tools and techniques: scanning, tokenization, redaction, de-identification.
  • Familiarity with Data Mesh or federated governance models: domain ownership, data as a product, self-serve platforms, governance as guardrails (not gates).

Bonus Points

• Experience with Azure/Databricks → GCP migrations, especially governance and cost remediation during migration.
• Knowledge of ML governance: feature stores, model lineage, experiment tracking, model monitoring, responsible AI practices.
• Contributions to open-source data governance or quality frameworks (Great Expectations, dbt packages, OpenLineage, Amundsen, Datahub, etc.).
• Experience with FinOps certification or formal FinOps programs (cloud cost management, budget forecasting, optimization strategies).
• Background in compliance audits or enterprise data governance programs (ISO 27001, SOC 2, PCI-DSS).

Why Join Us

You'll join a company with global ambitions and a highly motivated Data team at a critical inflection point: migrating to a modern cloud stack and building the governance, cost discipline, and enablement culture that will scale for years to come.

Here, you won't just implement tools—you'll architect the foundations of how Blip governs, optimizes, and democratizes data. You'll work directly with Google Cloud Professional Services, shape corporate standards, and enable dozens of engineers and analysts to build faster, safer, and smarter.

This is a rare opportunity to be the "governance engineer" who makes governance loved, not feared.

Informações adicionais

SOBRE A CAPCO

A Capco é uma consultoria global de tecnologia e gestão especializada na transformação digital, oferecendo soluções inovadoras e orientadas por dados para um portfólio crescente de mais de 100 clientes globais, entre eles bancos, pagamentos, mercados de capitais, gestão de patrimônio e ativos, seguros e setor de energia.

Nos destacamos pela abordagem personalizada, focada na construção de parcerias estratégicas de longo prazo e na aceleração de iniciativas digitais. Nossa expertise ganha vida por meio dos Innovation Labs e da cultura premiada Be Yourself At Work, que valoriza a diversidade e o talento.

Com presença global nos principais centros financeiros - temos 33 escritórios nas Américas, Europa e Ásia-Pacífico - estamos comprometidos em oferecer soluções práticas e integradas, promovendo colaboração e confiança em cada projeto. Se criatividade e inovação são sua paixão, a Capco é ideal para você. Vamos te apoiar e ajudar a acelerar sua carreira!

Sobre a oportunidade: 

Estamos em busca de um(a) Senior Consultant com experiência sólida em Business Analysis com plataformas de Big Data e vivência em ambientes de Cloud. Esta é uma excelente oportunidade para profissionais técnicos que desejam atuar em projetos de alto impacto, com foco em soluções escaláveis, processamento de grandes volumes de dados e modernização de ambientes analíticos.

Requisitos Desejáveis:

• Experiência com Data Lake, Delta Lake e arquiteturas orientadas a eventos.
• Certificações em Cloud (ex: AWS Certified Data Analytics, Azure Data Engineer, etc.).
• Conhecimentos em linguagens como Python, Scala ou Java voltadas para processamento de dados.
• Familiaridade com ferramentas de orquestração como Airflow, Apache Nifi, DBT ou similares.
• Entendimento de boas práticas de governança de dados, segurança e compliance.

POR QUE CAPCO:

Juntar-se à Capco significa ingressar em uma organização comprometida com um ambiente de trabalho inclusivo onde você é incentivado a #BeYourselfAtWork (Ser Você Mesmo no Trabalho). Celebramos a individualidade e reconhecemos que a diversidade e a inclusão, em todas as formas, são fundamentais para o sucesso. Acreditamos que todos trazem algo diferente, por isso adoraríamos saber o que o torna diferente!

Estamos em busca de um(a) Business Analyst com forte atuação em projetos de dados, capaz de traduzir necessidades de negócio em requisitos técnicos e análises estratégicas. O(a) profissional ideal terá experiência em ambientes de Big Data, conhecimento em ferramentas como Snowflake e Hadoop, e facilidade em interagir com áreas técnicas e de negócio.

Responsabilidades:

• Levantar, mapear e analisar requisitos de negócio voltados a dados e analytics;

• Traduzir necessidades das áreas de negócio em histórias de usuário e requisitos técnicos claros;

• Trabalhar em parceria com times de engenharia de dados, ciência de dados e produto;

• Realizar análises exploratórias de dados e gerar insights acionáveis;

• Documentar processos, fluxos de dados e regras de negócio;

• Apoiar o desenho de soluções de dados com foco em escalabilidade e performance;

• Garantir a qualidade e integridade das entregas de dados (requisitos, relatórios, dashboards, etc.).

Requisitos:

• Experiência prévia como Business Analyst ou Product Analyst em projetos de dados;

• Familiaridade com ambientes de Data Warehouse e Data Lake;

• Conhecimento em ferramentas como Snowflake, Hadoop, Hive, Spark, etc.;

• Experiência com análise de dados utilizando SQL avançado;

• Capacidade de leitura e entendimento de pipelines de dados;

• Habilidade de comunicação com perfis técnicos e não técnicos;

• Conhecimento de metodologias ágeis (Scrum/Kanban).

• Inglês avançado.

Diferenciais:

• Experiência com ferramentas de BI (Power BI, Tableau, Looker);

• Noções de modelagem de dados (dimensional, relacional, etc.);

• Experiência em ambientes Cloud (AWS, GCP ou Azure);

• Experiência em projetos de governança de dados ou compliance (LGPD, GDPR).

PRÓXIMOS PASSOS:

O objetivo da Capco é conduzir um processo flexível e alinhado às necessidades de cada oportunidade e talento.

• Etapa 1: Entrevista comportamental.
• Etapa 2: Entrevista técnica.
• Etapa 3: Conversa com time de Projeto/ Delivery.
• Etapa 4: Conversa com cliente.
• Etapa 5: Proposta ou feedback.

As etapas do nosso processo seletivo descritas são essenciais para garantir uma avaliação completa e assertiva. Contudo, elas podem ser ajustadas dependendo da senioridade do(a) candidato(a), da área de atuação e do formato do projeto.