At CI&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 & AI Martech and Business strategy. We are 8000 CI&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. 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. Responsibilities Delivery & 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. 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. Dimensional Modeling Design and implement dimensional modeling artifacts — facts dimensions and slowly changing dimensions — with a clear understanding of how they enable downstream reporting. Workflow Management Make changes to data processing jobs and workflows as needed to support evolving business requirements. Code Review & Quality Review pull requests from other developers enforcing code quality performance and architectural consistency across the codebase. Environment & 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. Production Monitoring & Troubleshooting Monitor and troubleshoot daily production jobs investigating failures and performance issues using platform-native diagnostic tools job logs and table history. Testing & Automation Maintain and improve the automated testing pipeline including CI/CD workflows and the underlying test framework. Documentation Keep technical documentation current so institutional knowledge is not lost as the pipelines and connections the team relies on evolve. Technical Reference & 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. 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. Requirements Solid experience in data development with proven hands-on production experience on the Databricks platform 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 Solid practical experience with Delta Lake MERGE/upsert patterns ACID transactions time travel and table maintenance (OPTIMIZE VACUUM ZORDER liquid clustering Change Data Feed) 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 Experience with medallion (or comparable layered) architecture in a production data platform and with Unity Catalog jobs/workflows secrets management and notebook-based development 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) 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 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 Nice to Have Experience with Databricks Asset Bundles or other Infrastructure-as-Code approaches for managing jobs clusters and permissions as code Familiarity with Delta Live Tables and with Databricks Genie (AI/BI Genie) for natural-language querying and conversational analytics Familiarity with data quality frameworks (e.g. Great Expectations Soda Core or custom validation frameworks) Experience with pytest and databricks-connect for automated testing of Spark pipelines outside of manual notebook execution Familiarity with Pydantic or similar typed-configuration approaches and experience with schema migration/versioning approaches (e.g. Flyway Liquibase or custom frameworks) Comfortable using AI-assisted development tools (e.g. GitHub Copilot Cursor or similar) to accelerate coding debugging and code review workflows #LI-JP3 ➡ ➡ Our benefits include - Premium Healthcare - Meal voucher - Maternity and Parental leaves - Mobile services subsidy - Sick pay-Life insurance - CI&T University - Colombian Holidays - Paid Vacations And many others. Collaboration is our superpower diversity unites us and excellence is our standard. We value diverse identities and life experiences fostering a diverse inclusive and safe work environment. We encourage applications from diverse and underrepresented groups to our job positions.