Lead Data Engineer
E
EncoraInsurance
BrazilFull-TimeLead
Salary not disclosed
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Job Details
- Required Skills
- AWSSQLGitSnowflakeAzureCI/CDTerraformdbt
Requirements
- Experience in Data Engineering
- Proven experience leading data engineering teams and delivering large-scale data platform initiatives
- Strong hands-on experience with Snowflake
- Strong hands-on experience with Azure Databricks
- Strong hands-on experience with DBT
- Deep expertise in cloud infrastructure
- Deep expertise in infrastructure-as-code tools, especially Terraform
- Extensive experience with cloud data migration projects (AWS to Azure preferred)
- Strong experience with CI/CD pipelines
- Strong experience with Git-based version control
- Advanced proficiency in SQL
- Advanced proficiency in data modeling
- Advanced proficiency in ETL/ELT design patterns
- Strong understanding of data architecture
- Strong understanding of scalability and performance optimization
- Mandatory experience in the insurance industry, with understanding of insurance data domains (policies, claims, underwriting, etc.)
Responsibilities
- Lead and mentor a team of data engineers, providing technical guidance, code reviews, and best practices
- Own the end-to-end data migration strategy from Snowflake on AWS to Azure Databricks and DBT, including planning, execution, and optimization
- Collaborate with cross-functional stakeholders (data, product, architecture, and business teams) to align data initiatives with organizational goals
- Architect and oversee scalable, secure, and reliable data pipelines and infrastructure in Azure
- Drive the design and implementation of infrastructure-as-code using Terraform, ensuring consistency and maintainability
- Ensure efficient data integration between Snowflake and Azure environments, establishing robust and scalable data flows
- Oversee data transformation frameworks using Databricks and DBT, promoting reusable and modular design patterns
- Establish and enforce data engineering standards, governance practices, and CI/CD workflows
- Proactively identify risks, troubleshoot complex technical issues, and implement long-term solutions
- Lead documentation efforts for architecture, processes, and best practices across the data platform
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