Senior Data Engineer
At a glance
Senior Data Engineering role at Blend360. Guadalajara · full-time.
Pay not stated Data Engineer salary
dataroles summary, based on the employer's posting.
What you'll do
- Keep GitHub repositories automated and easier to maintain by restructuring older code for reuse
- Build reusable code modules that support different journeys without duplicating work
- Create and manage Databricks pipelines that feed datasets into downstream reporting
- Bring journey KPIs, metrics and attributes into consistent structures for flexible analysis
- Maintain scalable analytics models and check pipeline and dataset quality, speed and reliability
What you bring
- At least five years in data engineering or a comparable role
- Hands-on pipeline development in Databricks or Snowflake, plus strong GitHub and version-control experience
- Experience improving legacy code and designing reusable components and analytics data models
- Strong written and spoken English for clear team communication
Who this fits
This senior role suits an independent engineer who can move initiatives forward with broad direction and limited supervision, while working with analytics and engineering teams. The position is hybrid in Guadalajara.
From the employer
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 .
Build, maintain, and optimize scalable data solutions to support initiatives, focusing on code maintainability, reusable components, and reliable data pipelines. This role is responsible for maintaining and refactoring existing codebases, developing modular components, and ensuring high-quality, performant datasets for analytics and reporting use cases.
The ideal candidate has strong experience working with code repositories, building data pipelines in Databricks or Snowflake, and designing scalable data models to support evolving analytics needs in cross-functional environments.
Responsibilities
- Maintain, optimize, and automate existing code repositories in GitHub.
- Refactor legacy code to simplify maintenance, updates, and reuse across multiple use cases.
- Design and build modular, reusable code components to support multiple journeys and reduce duplication.
- Develop and manage automated data pipelines in Databricks to support datasets and downstream reporting.
- Consolidate key KPIs, metrics, and attributes into standardized data structures to enable flexible journey views.
- Build and maintain scalable data models to support current and future journey analytics use cases.
- Ensure data quality, performance, and reliability across data pipelines and analytics datasets.
- Collaborate with analytics and engineering teams to improve data processes and architecture.
- Strong experience working with GitHub repositories and version control workflows.
- Hands-on experience developing and maintaining data pipelines in Databricks or Snowflake.
- 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.
What about languages?
- You will need excellent written and verbal English for clear and effective communication with the team.
How much experience must I have?
- In order to thrive in this role, you must have at least 5+ years of experience in data engineering or similar roles.
Our Perks and Benefits
📚Learning Opportunities:
- 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.
👩🏫 Mentoring and Development:
- Career development plans and mentorship programs to help shape your path.
🎁 Celebrations & Support:
- 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.
So what are the next steps?
Our team is eager to learn about you! Send us your resume or LinkedIn profile below and we’ll explore working together!
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