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

CI&T; United States; Remote; USD 120,000 - 180,000; Full time

Benefits offered by this job

Premium Healthcare

Meal vouchers

Maternity leave

Parental leave

Mobile subsidy

Life insurance

CI&T University

Colombian Holidays

Paid vacations

Job summary

CI&T is seeking a Senior Data Developer (Databricks) to own a mission-critical data platform supporting business reporting and analytics for our client. You will work deeply in the Databricks ecosystem across ingestion to a modeled dimensional layer, serving as the technical backbone for the team.

You will lead architecture suggestions, review code, troubleshoot production jobs, and ensure robust deployment and documentation practices across Dev, QA, UAT, and PROD environments.

Qualifications

• Solid hands-on production experience on the Databricks platform.
• Proficiency in PySpark and Spark SQL with performance tuning.
• Experience with Delta Lake and ACID transactions.
• Understanding of Slowly Changing Dimensions and dimensional modeling concepts.
• Experience with medallion architecture, notebooks, and Unity Catalog.
• Familiarity with Git and CI/CD pipelines in Azure environment.
• Strong English communication and ability to work with US stakeholders.

Responsibilities

• Own and evolve notebooks across Stage, Bronze, Silver, and Gold layers for BI reporting.
• Design and implement dimensional modeling artifacts to support downstream reporting.
• Review PRs, enforce code quality, and maintain architectural consistency.
• Deploy and promote changes across Dev/QA/UAT/Prod environments.
• Monitor production jobs and troubleshoot failures with platform tools.
• Improve CI/CD pipelines and automated tests for data pipelines.
• Maintain up-to-date technical documentation.
• Be the technical reference for the data platform and mentor teammates.
• Collaborate with client stakeholders to translate requirements into scalable pipelines.

Skills

PySpark

Databricks

Spark SQL

Delta Lake

Dimensional modeling

Medallion architecture

Azure Data Services

Git & DevOps

Python

English communication

Tools

Git

Azure DevOps

Unity Catalog

Job description

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 8,000 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.