Data Engineer Manager

Lead, design, and scale data solutions to support Journey Analytics initiatives, with a strong focus on code quality, reusability, and reliable data platforms. This role is responsible for setting the technical direction, overseeing the evolution of data architectures, and leading a team of data engineers to deliver high-quality, performant datasets for analytics and reporting use cases.

The ideal candidate combines strong hands-on data engineering expertise with people leadership experience, and has a proven track record of driving scalable solutions in cross-functional environments.
Responsibilities

- Lead and 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 the 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 the 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.

- 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).

- Certifications in AWS (we are AWS Partners), Databricks, and Snowflake.

- 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. For detailed information regarding the benefits applicable to your specific location, please consult with one of our recruiters.

Blend is a premier AI services provider, committed to co-creating meaningful impact for its clients through the power of data science, AI, technology, and people. With a mission to fuel bold visions, Blend tackles significant challenges by seamlessly aligning human e