Big Data Engineer handling both internal and external stakeholders for data processing related to fraud and compliance at ING. Managing and transforming high volume data and working closely with project teams.
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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