We’re an AI-first global tech company with 25+ years of engineering leadership, 2,000+ team members, and 500+ active projects powering Fortune 500 clients, including HBO, Microsoft, Google, and Starbucks.
From AI platforms to digital transformation, we partner with enterprise leaders to build what’s next.
What powers it all? Our people are ambitious, collaborative, and constantly evolving.
A leading global digital banking platform and one of the largest neobanks in Latin America, headquartered in Brazil. The company provides a mobile-first suite of financial services—including credit cards, savings accounts, and investments—designed to eliminate bureaucracy and high fees. By leveraging advanced data analytics and a customer-centric digital infrastructure, the organization delivers transparent and accessible financial solutions to millions of users across Brazil, Mexico, and Colombia.
What You’ll Do- Design, develop, and maintain scalable, production-grade data pipelines integrating SaaS platforms, APIs, batch processes, and enterprise data sources.
- Transform, integrate, standardize, and model structured and semi-structured data from multiple heterogeneous systems.
- Develop and optimize data processing solutions using Databricks and Apache Spark for large-scale distributed data processing.
- Design and implement reliable dimensional data models, including Fact, Dimension, and Event tables, following modern Data Engineering and Data Warehouse best practices.
- Build trusted, analytics-ready datasets and business metrics that serve as a Single Source of Truth for analytical and business use cases.
- Develop incremental, idempotent, scalable, and maintainable data pipelines.
- Optimize data processing workloads, queries, and pipeline performance with a focus on scalability and efficiency.
- Implement automated data quality, validation, testing, monitoring, and observability practices.
- Troubleshoot production issues, investigate root causes, and implement sustainable solutions to improve reliability and operational excellence.
- Validate data reconciliation between legacy and modern cloud platforms throughout migration initiatives.
- Collaborate closely with Data Engineers, Software Engineers, Analytics teams, Product teams, and other cross-functional stakeholders.
- Take end-to-end ownership of technical solutions, from design and development through deployment, production support, and continuous improvement.
- Contribute to CI/CD, code reviews, automated testing, and modern software engineering practices.
- Leverage AI-assisted development tools to accelerate coding, testing, troubleshooting, documentation, and other engineering activities while applying sound technical judgment.
- Identify opportunities to improve automation, platform reliability, engineering productivity, and data quality.
- Produce technical documentation and facilitate knowledge sharing and knowledge transfer across engineering teams.
- Professional experience in Data Engineering, Analytics Engineering, or a related field.
- Proven experience building and operating production-grade data pipelines.
- Strong hands-on experience with Databricks, including Workflows, Jobs, and Unity Catalog.
- Advanced experience with Apache Spark, using PySpark and/or Scala.
- Experience processing and optimizing large-scale datasets, including datasets containing hundreds of millions of records.
- Advanced SQL skills, including complex queries, data transformations, and query optimization.
- Strong understanding of data modeling and analytical data structures, including Fact and Dimension tables, SCD, and data grain.
- Strong knowledge of Delta Lake and/or Apache Iceberg.
- Experience building incremental and idempotent data pipelines.
- Experience implementing data quality, validation, testing, monitoring, and observability practices.
- Strong troubleshooting and production support experience.
- Experience with Git, CI/CD pipelines, automated testing, code reviews, and modern software engineering practices.
- Strong analytical and problem-solving skills.
- Good communication skills and the ability to clearly communicate technical concepts and solutions.
- Experience supporting cloud migration and data modernization initiatives, particularly migrations from GCP to AWS.
- Experience with AWS services, including S3, Glue, and Lake Formation.
- Familiarity with Google Cloud Platform (GCP) or other major cloud platforms.
- Experience with modern Lakehouse architectures and Semantic Layer concepts.
- Experience integrating REST APIs and processing JSON data.
- Knowledge of Data Governance principles and practices.
- Experience with Infrastructure as Code (IaC) tools such as Terraform.
- Experience with data observability and monitoring tools.
- Experience working with sensitive HR/People data and familiarity with LGPD, GDPR, or similar data privacy regulations.
- Familiarity with modern AI-assisted development tools and workflows.
Advanced English proficiency
Work Type: Hybrid
Location: São Paulo
Legal & Hiring Information- Exadel is proud to be an Equal Opportunity Employer committed to inclusion across minority, gender identity, sexual orientation, disability, age, and more
- Reasonable accommodations are available to enable individuals with disabilities to perform essential functions
- Please note: this job description is not exhaustive. Duties and responsibilities may evolve based on business needs
- Compensation details are shared with candidates at the early stage of the recruitment process.
- The offer is not binding until a signed contract is in place.
Exadel benefits vary by location and contract type. Your recruiter will fill you in on the details.
- International projects
- In-office, hybrid, or remote flexibility
- Medical healthcare
- Recognition program
- Ongoing learning & reimbursement
- Well-being program
- Team events & local benefits
- Sports compensation
- Referral bonuses
- Top-tier equipment provision
We lead with trust, respect, and purpose. We believe in open dialogue, creative freedom, and mentorship that helps you grow, lead, and make a real difference. Ours is a culture where ideas are challenged, voices are heard, and your impact matters.
Skills Required
- Professional experience in data engineering, analytics engineering, or a related field
- Experience building and operating production-grade data pipelines
- Hands-on experience with Databricks, including Workflows, Jobs, and Unity Catalog
- Advanced Apache Spark experience using PySpark and/or Scala
- Experience processing and optimizing large-scale datasets, including hundreds of millions of records
- Advanced SQL skills, including complex queries, data transformations, and query optimization
- Strong understanding of data modeling, Fact and Dimension tables, SCD, and data grain
- Knowledge of Delta Lake and/or Apache Iceberg
- Experience building incremental and idempotent data pipelines
- Experience implementing data quality, validation, testing, monitoring, and observability practices
- Strong troubleshooting and production support experience
- Experience with Git, CI/CD pipelines, automated testing, and code reviews
- Strong analytical and problem-solving skills
- Good communication skills and ability to explain technical concepts and solutions
- Advanced English proficiency
- Experience supporting cloud migration and data modernization initiatives, particularly GCP to AWS migrations
- Experience with AWS services including S3, Glue, and Lake Formation
- Familiarity with Google Cloud Platform or other major cloud platforms
- Experience with modern Lakehouse architectures and Semantic Layer concepts
- Experience integrating REST APIs and processing JSON data
- Knowledge of data governance principles and practices
- Experience with Infrastructure as Code tools such as Terraform
- Experience with data observability and monitoring tools
- Experience handling sensitive HR/People data and familiarity with LGPD, GDPR, or similar privacy regulations
- Familiarity with modern AI-assisted development tools and workflows
Exadel Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Exadel and has not been reviewed or approved by Exadel.
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Fair & Transparent Compensation — Pay is considered competitive for certain roles and locations, with timely and predictable payroll practices. Compensation ranges align to market in higher‑cost geographies and senior tracks, indicating offers can be strong when role and market justify it.
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Healthcare Strength — U.S. medical insurance options are described positively, with health coverage and PTO called out as standouts. Company materials and third‑party listings consistently include comprehensive healthcare as a core benefit.
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Wellbeing & Lifestyle Benefits — Flexible, remote‑first norms and outcome‑based work are positioned as core benefits. Learning support such as paid certifications, courses, and conferences is emphasized, alongside a well‑being program.
Exadel Insights
What We Do
For more than 20 years, Exadel has been delivering Digital Transformation services, enterprise and custom software solutions for Fortune 500 clients, including HPE, Deloitte, Home Depot and McKesson. With 20+ locations and delivery centers across the US and Europe, Exadel solves the most complex engineering problems using Agile methodologies, offering a scalable and skilled mix of multi-shore resources at the industry's most competitive price. Exadel’s digital transformation solutions and services help chart new strategies that are built upon creative thinking, cutting-edge design, and technical innovation, designed for the growing digital landscape of business. Enterprise Services - Digital Transformation Experts - Developing mission-critical software and mobile applications - Advising companies on how best to leverage open source technology - Helping companies plan and implement migrations to better technology stacks - Providing QA, automation, and testing services for application development - Supporting and maintaining applications and systems for companies - Providing on-line training and mentoring to companies - Assisting companies in evaluating their current enterprise software architecture and planning for improvements or new systems.
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