Blend360
Technology
DataEngineerManager
Neural analysis suggests this role is
optimal for mid candidates.
“Data Engineer Manager at Blend360. Skills: Data engineering, Data platforms, People leadership. Lead and mentor a team of data engineers. Foster best practices in coding”
Industry & Context.
Identify risks; Identify bottlenecks; Identify improvement opportunities
Travel opportunities
What They're Looking For.
Must Have
7+ years of experience in Data Engineering, Experience working with GitHub repositories, Hands-on experience developing and maintaining data pipelines in Databricks, Proven experience refactoring and maintaining legacy codebases, Understanding of data modeling, Experience building scalable data models, Focus on data quality, Focus on data performance, Focus on data reliability, Ability to work in cross-functional environments, Ability to work independently, Ability to take ownership of initiatives, Drive tasks forward with minimal supervision
Nice to Have
Experience using Genie (Databricks)
What You'll Do.
Lead and mentor a team of data engineers
Foster best practices in coding
Foster best practices in architecture
Foster best practices in data engineering standards
Define technical strategy for Journey Analytics data platforms
Drive technical strategy for Journey Analytics data platforms
Ensure scalability of data platforms
Ensure maintainability of data platforms
Ensure performance of data platforms
Oversee maintenance of code repositories
Oversee optimization of code repositories
Oversee automation of code repositories
Ensure high-quality development practices
Ensure consistent development practices
Guide refactoring of legacy codebases
Improve maintainability of codebases
Improve scalability of codebases
Improve reusability of codebases
Drive design of modular data components
Drive design of reusable data components
Support multiple journeys with data components
Reduce duplication with data components
Oversee development of automated data pipelines
Oversee management of automated data pipelines
Ensure reliability of data pipelines
Ensure scalability of data pipelines
Establish standards for scalable data modeling
Enforce standards for scalable data modeling
Support current analytics use cases
Support future analytics use cases
Ensure data quality across data pipelines
Ensure data quality across datasets
Ensure governance across data pipelines
Ensure governance across datasets
Ensure performance across data pipelines
Ensure performance across datasets
Ensure reliability across data pipelines
Ensure reliability across datasets
Partner with analytics stakeholders
Partner with product stakeholders
Partner with engineering stakeholders
Align data solutions with business needs
Align data solutions with business priorities
Proactively identify risks
Proactively identify bottlenecks
Proactively identify improvement opportunities
Drive mitigation strategies at team level
Drive mitigation strategies at platform level
Promote continuous improvement of data processes
Promote continuous improvement of documentation
Promote continuous improvement of engineering practices
How You'll Work.
Team & Collaboration
Cross-functional environments; Analytics stakeholders; Product stakeholders; Engineering stakeholders
Full Job Description
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 expertise with artificial intelligence. The company is dedicated to unlocking value and fostering innovation for its clients by harnessing world-class people and data-driven strategy. We believe that the power of people and AI can have a meaningful impact on your world, creating more fulfilling work and projects for our people and clients. For more information, visit [www.blend360.com](http://www.blend360.com/) 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
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