Ciandt

At CI&amp;T, we help large enterprises transform the potential of AI into real business impact with AI Deployment, AI-native execution, and tech-integrated business solutions.
With 30 years of experience in technological transformation, we accelerate innovation with expertise in Agentic SDLC, Application modernization, Data &amp; AI, Martech and Business strategy.
We are 8,000 CI&amp;Ters across more than 25 countries, collaborating to build solutions with real impact. AI is already part of how we work, evolve, and innovate every day.<div> </div><div>
As CI&amp;T continues to grow its data practice, we are looking for a skilled Data Developer to join a team supporting data initiatives for a client in the consumer electronics and audio technology industry. This role is central to keeping the client's data reliable, well-modeled, and ready to power analytics and reporting across the business.
The Data Developer will work hands-on with existing data models and transformation workflows, turning business and analytical requirements into accurate, trustworthy datasets. The position combines technical depth in data transformation with strong collaboration skills, partnering closely with data developers, analysts, and business stakeholders to keep data pipelines running smoothly and to resolve issues as they arise.
Responsibilities:
<ul>
<li>Develops and maintains data transformations using SQL and dbt (or similar data transformation frameworks) to keep datasets accurate and up to date.</li>
<li>Queries, transforms, and validates data in Snowflake to support analytics and reporting needs.</li>
<li>Builds and maintains data models that support business and analytical requirements.</li>
<li>Investigates data quality, consistency, and accuracy issues by tracing data back through pipelines and transformation logic to identify root causes.</li>
<li>Analyzes and optimizes SQL queries and data transformations to improve performance and reliability.</li>
<li>Collaborates with data developers and analysts to understand data requirements and support the onboarding of new data sources.</li>
<li>Translates business and analytical requirements into reliable, well-documented datasets and data models.</li>
<li>Follows established data modeling, testing, documentation, and development best practices.</li>
<li>Supports the maintenance and continuous improvement of existing data pipelines and transformation workflows.</li>
<li>Contributes to analytics and reporting solutions, including dashboard support when required, without this being the core focus of the role.</li>
<li>Communicates data requirements, blockers, and issues clearly to both technical and business stakeholders.</li>
</ul>
Requirements:
<ul>
<li>Advanced English proficiency (B2 or above), written and verbal, to participate in client meetings and discussions.</li>
<li>Solid, hands-on experience with SQL for querying, transforming, and validating data.</li>
<li>Practical experience working with Snowflake or a similar cloud data warehouse.</li>
<li>Hands-on experience with dbt or a similar data transformation framework.</li>
<li>Working knowledge of data modeling concepts and ETL/ELT (Extract, Transform, Load / Extract, Load, Transform) principles.</li>
<li>Demonstrated ability to investigate and troubleshoot data quality and consistency issues.</li>
<li>Strong analytical and problem-solving skills, with comfort working within existing data models and transformation workflows.</li>
<li>Good communication skills, with the ability to translate business and analytical requirements into technical deliverables.</li>
</ul>
Nice to Have:
<ul>
<li>Experience with Tableau or other BI/dashboarding tools.</li>
<li>Experience creating or maintaining dashboards and reports.</li>
<li>Familiarity with dbt testing, documentation, and data lineage practices.</li>
<li>Experience with Git and basic CI/CD (Continuous Integration/Continuous Deployment) workflows.</li>
<li>Exposure to modern data stack practices.</li>
<li>Experience working with product analytics, customer behavior, or operational data. #LI-JP3</li>
</ul>
</div>

[Job -  31120] Mid Level Data Developer, Colombia

[Job -  31120] Mid Level Data Developer, Brazil

At CI&amp;T, we help large enterprises transform the potential of AI into real business impact with AI Deployment, AI-native execution, and tech-integrated business solutions.
With 30 years of experience in technological transformation, we accelerate innovation with expertise in Agentic SDLC, Application modernization, Data &amp; AI, Martech and Business strategy.
We are 8,000 CI&amp;Ters across more than 25 countries, collaborating to build solutions with real impact. AI is already part of how we work, evolve, and innovate every day.<div> </div> 
At CI&amp;T, we combine human expertise with AI to build scalable and innovative technology solutions for global clients. We are looking for a Senior Data Engineer with strong experience in Azure cloud, SQL, Python, Data Warehouse, and modern data engineering practices to join our international team.
This role is ideal for professionals who enjoy working with scalable data pipelines, cloud-based data platforms, data quality, governance, and analytics enablement in complex enterprise environments.
<h3>Responsibilities</h3>
<ul>
<li>
Design, develop, and maintain scalable ETL/ELT pipelines in Azure environments.
</li>
<li>
Build and optimize Data Lake and Data Warehouse solutions to support analytics and business intelligence initiatives.
</li>
<li>
Develop and maintain data integration and orchestration pipelines using Azure Data Factory or similar tools.
</li>
<li>
Implement data quality validation, monitoring, and cleansing processes to ensure reliable and trustworthy data.
</li>
<li>
Create and maintain dimensional data models (Star Schema), including SCD Type 1 and Type 2 strategies.
</li>
<li>
Develop Python-based integrations and automations, including REST API consumption and data transformation workflows.
</li>
<li>
Implement CI/CD pipelines for data solutions and support automated deployment processes.
</li>
<li>
Apply Data Governance best practices, including data lineage, cataloging, access control, and data ownership.
</li>
<li>
Collaborate with international stakeholders, analysts, data scientists, and engineering teams to deliver high-quality data solutions.
</li>
<li>
Contribute to performance optimization and FinOps initiatives for cloud-based data platforms.
</li>
</ul>
<h3>Required Qualifications</h3>
<ul>
<li>
Advanced / Fluent English (C1 or higher).
</li>
<li>
Experience working with international clients or global projects.
</li>
<li>
Strong experience with Azure cloud services, including: Azure Data Factory (ADF), ADLS Gen2, Azure SQL Database,  Azure Functions, Azure Key Vault,  Azure Logic Apps
</li>
<li>
Advanced knowledge of SQL / T-SQL, including: CTEs, Window Functions,  MERGE statements,  Stored Procedures,  Change detection and incremental loading strategies
</li>
<li>
Strong experience with Python for: Data transformation, REST API integrations, JSON processing, Parquet generation, Error handling and retry patterns
</li>
<li>
Solid understanding of Data Lake, Data Warehouse, and dimensional modeling concepts.
</li>
<li>
Experience implementing Data Quality practices, such as completeness checks, referential integrity validation, and anomaly detection.
</li>
<li>
Familiarity with Git and CI/CD pipelines for data projects.
</li>
<li>
Understanding of Data Governance principles, including lineage, cataloging, security, and access management.
</li>
</ul>
<h3>Nice to Have</h3>
<ul>
<li>
Experience with Apache Spark / PySpark.
</li>
<li>
Knowledge of Azure DevOps or GitHub Actions for DataOps and CI/CD.
</li>
<li>
Experience with cloud-based modern data stacks.
</li>
<li>
Familiarity with FinOps practices applied to data platforms.
</li>
<li>
Experience with multi-entity or multi-source enterprise data environments.
</li>
<li>
Knowledge of Data Catalog and Lineage tools.
</li>
</ul>
<h3>What You’ll Find</h3>
<ul>
<li>
Challenging projects in large-scale enterprise data environments.
</li>
<li>
Opportunity to work with modern Azure data technologies and cloud-native architectures.
</li>
<li>
Collaborative and multicultural teams.
</li>
<li>
Continuous learning, technical growth, and participation in strategic data transformation initiatives.
</li>
</ul>
If you are passionate about Azure, SQL, Python, scalable data pipelines, and modern Data Engineering practices, we would love to hear from you!
<h2> </h2>
<div>#LI-LL1</div>

[Job-31000] Senior Data Engineer, Brazil

At CI&amp;T, we help large enterprises transform the potential of AI into real business impact with AI Deployment, AI-native execution, and tech-integrated business solutions.
With 30 years of experience in technological transformation, we accelerate innovation with expertise in Agentic SDLC, Application modernization, Data &amp; AI, Martech and Business strategy.
We are 8,000 CI&amp;Ters across more than 25 countries, collaborating to build solutions with real impact. AI is already part of how we work, evolve, and innovate every day.<div> </div><div>
We are looking for an experienced AI Engineer to build, integrate, and ship AI-powered features across enterprise-grade digital solutions. At its core, this is a hands-on senior developer role: you will write production code, integrate AI capabilities into real products, and raise the team's delivery speed through AI-accelerated engineering practices. The candidate is expected to be comfortable working with tools and solutions linked to the PHP and JavaScript languages, but not restricted to them, and to have solid hands-on experience. Knowledge and practical experience with AI solutions and an SDLC accelerated by AI are expected.
 Key Responsibilities &amp; Requirements
 AI-accelerated SDLC: Use AI coding tools and agentic workflows in day-to-day delivery (code generation, review, testing, documentation), and help the team adopt them consistently. Software programming: Strong command of high-level programming languages and deep experience with programming logic, clean code, and testing. Solution design: Design and document the components, workflows, data flows, and integration layers of the features you build, ensuring scalability, modularity, and performance. Requirements: Experience analysing functional and non-functional requirements, negotiating trade-offs, and making technical decisions. CMS: Familiarity with CMS (Content management system) concepts, headless architectures, and integration with front-end frameworks. Advanced English for communication.
Desirable
 AI-driven use cases: Experience with intelligent content features such as personalization engines or content recommendations using AI. Familiarity with Spec-Driven Development. Experience with headless CMS (Storyblok, Sanity.io). Experience with AI evaluation and observability (prompt versioning, regression testing, tracing). Experience with AI agent frameworks and MCP (Model Context Protocol) integrations.
 
#LI-BM2
</div>

[Job-30841] AI Engineer, Brazil

At CI&amp;T, we help large enterprises transform the potential of AI into real business impact with AI Deployment, AI-native execution, and tech-integrated business solutions.
With 30 years of experience in technological transformation, we accelerate innovation with expertise in Agentic SDLC, Application modernization, Data &amp; AI, Martech and Business strategy.
We are 8,000 CI&amp;Ters across more than 25 countries, collaborating to build solutions with real impact. AI is already part of how we work, evolve, and innovate every day.<div> </div><div>
We are seeking a Senior Data Developer (Databricks) to join our team and take ownership of a mission-critical data platform supporting business reporting and analytics for our client. This is an opportunity to work deep in the Databricks ecosystem — from raw ingestion through a fully modeled dimensional layer — while acting as the technical backbone the rest of the team relies on for platform expertise.
This role blends hands-on execution with technical leadership: you will own and evolve notebooks across the full medallion architecture, design and extend dimensional modeling artifacts that power downstream business intelligence, and serve as the primary reviewer and technical reference point for the team. You'll operate both strategically — proposing architectural and process improvements — and operationally — troubleshooting production jobs, deploying across environments, and keeping documentation current. Success in this role requires the ability to ramp up quickly in a large, established, business-rule-heavy codebase and start contributing meaningfully within a short window.
<h3>Responsibilities</h3>
<ul>
<li>
Delivery &amp; Continuous Improvement: Work on assigned tickets and bugs while continuously looking for improvement opportunities beyond the immediate task — proactively identifying tech debt, refactoring opportunities, and automation gaps rather than limiting contributions to what's assigned.
</li>
<li>
Data Pipeline Ownership: Own and evolve notebooks across the Stage, Bronze, Silver, and Gold layers, from ingestion through the dimensional model consumed by business intelligence reporting tools.
</li>
<li>
Dimensional Modeling: Design and implement dimensional modeling artifacts — facts, dimensions, and slowly changing dimensions — with a clear understanding of how they enable downstream reporting.
</li>
<li>
Workflow Management: Make changes to data processing jobs and workflows as needed to support evolving business requirements.
</li>
<li>
Code Review &amp; Quality: Review pull requests from other developers, enforcing code quality, performance, and architectural consistency across the codebase.
</li>
<li>
Environment &amp; Deployment Management: Deploy and promote changes across environments (Dev, QA, UAT, PROD), keeping deployment tracking up to date, and support environment operations such as restoring environments or tables from another environment or from a specific point in time.
</li>
<li>
Production Monitoring &amp; Troubleshooting: Monitor and troubleshoot daily production jobs, investigating failures and performance issues using platform-native diagnostic tools, job logs, and table history.
</li>
<li>
Testing &amp; Automation: Maintain and improve the automated testing pipeline, including CI/CD workflows and the underlying test framework.
</li>
<li>
Documentation: Keep technical documentation current so institutional knowledge is not lost as the pipelines and connections the team relies on evolve.
</li>
<li>
Technical Reference &amp; Mentoring: Act as the go-to technical reference for the team on the data platform — the person others turn to when something needs deep platform expertise — and support other team members on data modeling and development topics.
</li>
<li>
Stakeholder Collaboration: Propose and recommend architectural and process improvements, collaborating with the client's business and technical stakeholders — including the client's data architecture function — to translate requirements into scalable, well-tested data pipelines, while remaining equally comfortable taking direction from client-side technical leadership.
</li>
</ul>
<h3>Requirements</h3>
<ul>
<li>
Solid experience in data development, with proven hands-on production experience on the Databricks platform
</li>
<li>
Strong proficiency in PySpark (DataFrame API, Spark SQL, UDFs, window functions) and Databricks SQL (ANSI SQL, MERGE INTO, COPY INTO, CTEs), including performance tuning such as partition pruning, file compaction, skew handling, and query optimization
</li>
<li>
Solid, practical experience with Delta Lake: MERGE/upsert patterns, ACID transactions, time travel, and table maintenance (OPTIMIZE, VACUUM, ZORDER, liquid clustering, Change Data Feed)
</li>
<li>
Demonstrated experience implementing Slowly Changing Dimensions (Type 1 and Type 2) and dimensional modeling concepts (star schema, fact/dimension design) — not requiring you to have designed a model from scratch, but requiring the mindset to understand and extend one
</li>
<li>
Experience with medallion (or comparable layered) architecture in a production data platform, and with Unity Catalog, jobs/workflows, secrets management, and notebook-based development
</li>
<li>
Experience with Git and Azure DevOps (or equivalent) for version control, pull requests, and CI/CD pipelines, along with Microsoft Azure services (Key Vault, Service Principal/Managed Identity, Data Lake Storage)
</li>
<li>
Ability to read and navigate a large, established codebase (400+ notebooks), learning and following existing conventions rather than rewriting them, and to ramp up quickly in a business-rule-heavy environment
</li>
<li>
Advanced English (C1 or above) communication skills, with the ability to work directly with US-based client stakeholders, propose technical recommendations, and align with decisions made by client-side technical leadership
</li>
</ul>
<h3>Nice to Have</h3>
<ul>
<li>
Experience with Databricks Asset Bundles or other Infrastructure-as-Code approaches for managing jobs, clusters, and permissions as code
</li>
<li>
Familiarity with Delta Live Tables and with Databricks Genie (AI/BI Genie) for natural-language querying and conversational analytics
</li>
<li>
Familiarity with data quality frameworks (e.g., Great Expectations, Soda Core, or custom validation frameworks)
</li>
<li>
Experience with pytest and databricks-connect for automated testing of Spark pipelines outside of manual notebook execution
</li>
<li>
Familiarity with Pydantic or similar typed-configuration approaches, and experience with schema migration/versioning approaches (e.g., Flyway, Liquibase, or custom frameworks)
</li>
<li>
Comfortable using AI-assisted development tools (e.g., GitHub Copilot, Cursor, or similar) to accelerate coding, debugging, and code review workflows
</li>
</ul>
<div> </div>
<div>#LI-JP3</div>
</div>

Ciandt

Open jobs at Ciandt

[Job - 31120] Mid Level Data Developer, Colombia

[Job - 31120] Mid Level Data Developer, Brazil

[Job-31000] Senior Data Engineer, Brazil

[Job-30841] AI Engineer, Brazil

[Job - 30813] Senior Data Developer (Databricks), Colombia

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