Blend360
Marketing And Advertising
DataEngineerManager
Neural analysis suggests this role is
optimal for mid candidates.
“Data Engineer Manager at Blend360. Skills: Data Engineering, Data Platforms, Team Leadership. Lead and mentor a team of data engineers. Foster best practices in coding”
Industry & Context.
Risk identification; Bottleneck identification; 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, understanding of reusable component design, Experience building scalable data models, focus on data quality, focus on performance, focus on reliability, Ability to work in cross-functional environments, Ability to contribute to continuous improvement, Ability to work independently, take ownership of initiatives, driving 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 and drive the technical strategy for Journey
Ensure scalability of data platforms
Ensure maintainability of data platforms
Ensure performance of data platforms
Oversee the maintenance of code repositories in GitHub
Oversee the optimization of code repositories in GitHub
Oversee the automation of code repositories in GitHub
Ensure high-quality development practices
Ensure consistent development practices
Guide the refactoring of legacy codebases
Improve maintainability of legacy codebases
Improve scalability of legacy codebases
Improve reusability of legacy codebases
Drive the design of modular data components
Drive the design of reusable data components
Support multiple journeys
Oversee the development of automated data pipelines in
Oversee the management of automated data pipelines in
Ensure reliability for downstream consumption
Ensure scalability for downstream consumption
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 all data pipelines
Ensure data quality across all datasets
Ensure governance across all data pipelines
Ensure governance across all datasets
Ensure performance across all data pipelines
Ensure performance across all datasets
Ensure reliability across all data pipelines
Ensure reliability across all 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 a team level
Drive mitigation strategies at a 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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