CI&T
[Job- 30340] Senior Data Developer (Analytics Engineer), Colombia
Vaga remota de Analytics Engineer com fit claro de localização do candidato.
Publicada9 de jul. de 2026
Países elegíveis1 país aceito
Sinal de senioridadeSenior
Modelo de trabalhoRemoto
Locais aceitos para candidatos
Colômbia
Resumo da vaga
[Job- 30340] Senior Data Developer (Analytics Engineer), Colombia
Requisitos e responsabilidades
Conteúdo da vaga extraído em seções para revisão mais rápida.
Responsibilities:
- Business Translation & Requirements Definition: Actively engage with business stakeholders to understand context, challenges, and underlying needs; translate complex requirements into clear, detailed technical specifications that enable effective use of AI and analytics platforms.
- End-to-End Product Ownership: Take full responsibility for the data products you build — from ingestion through modeling, transformation, validation, to final delivery and ongoing monitoring.
- Data Quality Assurance & Validation: Implement and maintain rigorous validation processes, automated testing, and quality checks; act as guardian of data accuracy and integrity, ensuring metrics and KPIs accurately reflect business reality.
- Data Modeling & Transformation: Design and implement data transformation layers that pre-aggregate business information, apply consistent business rules, and deliver datasets ready for consumption in dashboards and AI applications.
- AI Enablement & Data Structuring: Collaborate with AI teams to specify and prepare structured data, data dictionaries, and models that enable AI platforms and intelligent reporting capabilities.
- Full-Stack Data Development: Build and maintain data ingestion pipelines from multiple sources, implement transformations in SQL and Python, and ensure performance and scalability of solutions.
- Proactive Problem Solving: Go beyond fulfilling requirements — proactively identify improvement opportunities, anticipate internal customer needs, propose innovative solutions, and challenge approaches when necessary.
- Agile & High-Quality Delivery: Deliver reliable data solutions with speed and precision, balancing the need for rapid iteration with the highest quality standards.
- Stakeholder Communication: Articulate technical concepts clearly to non-technical audiences; facilitate alignments, present solution proposals, and document modeling and architecture decisions.
Requirements:
- Proven experience in a Data Engineering or Analytics Engineering role at senior level
- Advanced proficiency in SQL and Python for data analysis, transformation, and validation
- Solid experience in data modeling and data warehouse design
- Hands-on experience working with BigQuery (or other cloud-based data warehouse platform)
- Demonstrated ability to understand complex business logic and validate results from a business perspective, not just technical
- Strong sense of ownership and proactive mindset — a professional who proposes improvements, challenges requirements when necessary, and doesn't wait to be asked to act
- Experience specifying and preparing data requirements for AI or machine learning applications
- Advanced/fluent English (reading, writing, and conversation) — constant communication with international stakeholders is required
- Track record of delivering high-impact projects quickly and with quality
Nice to Have:
- Experience with dbt (data build tool) for transformation and orchestration of analytical pipelines
- Familiarity with data ingestion tools such as Airbyte or Airflow
- Knowledge of automated testing best practices and CI/CD for data pipelines
- Prior experience in Supply Chain, Retail, or Consumer Goods industries
- Experience in projects involving data preparation for consumption via generative AI or conversational analytics platforms
- Experience building business-oriented analytical reports (web reporting, custom visualizations)
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