Data Engineer developing automated data pipelines for Creditreform. Collaborating with Data Scientists and Analysts and ensuring data quality and consistency.
About the role
- Data Architect leading data strategy and analytics for clients while connecting technology, business, and governance. Requires expertise in modern data architecture and DataOps practices.
Responsibilities
- Define the data strategy and modernize the analytics platform
- Structure and lead multidisciplinary teams (engineering, data science, analytics, and governance)
- Implement DataOps practices and modern engineering
- Build technical and strategic credibility with the client
- Identify and lead data expansion opportunities
- Ensure technical excellence, scalability, and governance
- Design and evolve modern data architecture (batch and streaming)
- Define engineering and data science standards
- Establish DataOps adoption as an organizational practice
- Ensure scalability, security, governance, and reliability
- Lead decisions regarding the technology stack (Azure, Databricks, Synapse, Cosmos DB, etc.)
- Cover end-to-end aspects from ingestion and processing to consumption, governance, and data monetization
- Organize and develop data teams
- Mentor engineers and data scientists
- Raise the client's technical capabilities
- Identify opportunities for new projects
- Translate technical deliveries into a strategic expansion roadmap
Requirements
- Experience defining data strategy and modernizing analytics platforms
- Ability to structure and lead multidisciplinary teams (engineering, data science, analytics, and governance)
- Knowledge of DataOps practices and modern engineering
- Ability to build technical and strategic credibility with clients
- Experience identifying and leading data expansion opportunities
- Proven track record ensuring technical excellence, scalability, and governance
- Experience designing and evolving modern data architectures (batch and streaming)
- Ability to define engineering and data science standards
- Experience establishing DataOps as an organizational practice
- Ability to lead technology stack decisions (Azure, Databricks, Synapse, Cosmos DB, etc.)
- Understanding of end-to-end data flows from ingestion and processing to consumption, governance, and monetization
- Experience organizing and developing data teams
- Experience mentoring engineers and data scientists
- Ability to elevate the client's technical capabilities
- Experience identifying opportunities for new projects
- Ability to turn technical deliveries into a strategic expansion agenda
Benefits
- Health and dental insurance
- Meal and food allowances
- Childcare assistance
- Extended parental leave
- Partnerships with gyms and health & wellness professionals via Wellhub (Gympass) and TotalPass
- Profit-sharing (PLR)
- Life insurance
- Continuous learning platform (CI&T University)
- Employee discount club
- Free online platform dedicated to physical and mental health and wellbeing
- Pregnancy and responsible parenthood course
- Partnerships with online course platforms
- Language learning platform
- And many others
Job title
Job type
Experience level
Salary
Not specified
Degree requirement
Tech skills
Location requirements
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