Data Engineer Manager
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Job Description
Data Engineer Manager leading a team for Journey Analytics initiatives at Blend, an AI services provider. Focus on scalable data solutions and data engineering best practices.
Responsibilities:
- Lead, design, and scale data solutions to support Journey Analytics initiatives, with a strong focus on code quality, reusability, and reliable data platforms.
- Set the technical direction, oversee the evolution of data architectures, and lead a team of data engineers to deliver high-quality, performant datasets for analytics and reporting use cases.
- Mentor a team of data engineers, fostering best practices in coding, architecture, and data engineering standards.
- Define and drive the technical strategy for Journey Analytics data platforms, ensuring scalability, maintainability, and performance.
- Oversee maintenance, optimization, and automation of code repositories in GitHub, ensuring high-quality and consistent development practices.
- Guide the refactoring of legacy codebases to improve maintainability, scalability, and reusability across multiple use cases.
- Drive the design and implementation of modular, reusable data components to support multiple journeys and reduce duplication.
- Oversee development and management of automated data pipelines in Databricks, ensuring reliability and scalability for downstream consumption.
- Establish and enforce standards for scalable data modeling to support current and future analytics use cases.
- Ensure data quality, governance, performance, and reliability across all data pipelines and datasets.
- Partner with analytics, product, and engineering stakeholders to align data solutions with business needs and priorities.
- Proactively identify risks, bottlenecks, and improvement opportunities, and drive mitigation strategies at a team and platform level.
- Promote continuous improvement of data processes, documentation, and engineering practices.
Requirements:
- 7+ years of experience in Data Engineering.
- Strong experience working with GitHub repositories and version control workflows.
- Hands-on experience developing and maintaining data pipelines in Databricks.
- Proven experience refactoring and maintaining legacy codebases.
- Strong understanding of data modeling and reusable component design.
- Experience building scalable data models for analytics and reporting use cases.
- Strong focus on data quality, performance, and reliability.
- Ability to work in cross-functional environments and contribute to continuous improvement.
- Ability to work independently and take ownership of initiatives after receiving high-level direction, driving tasks forward with minimal supervision.
- Experience using Genie (Databricks) (Plus).
Benefits:
- Access to AI learning paths to stay up to date with the latest technologies.
- Study plans, courses, and additional certifications tailored to your role.
- Access to Udemy Business, offering thousands of courses to boost your technical and soft skills.
- English lessons to support your professional communication.
- Travel opportunities to attend industry conferences and meet clients.
- Career development plans and mentorship programs to help shape your path.
- Special day rewards to celebrate birthdays, work anniversaries, and other personal milestones.
- Company-provided equipment.
- Flexible working options to help you strike the right balance.
- Other benefits may vary according to your location in LATAM.
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