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Data Engineer Lead

Role overview

Qualifications

  • Hands-on experience developing and maintaining data pipelines in Databricks
  • Strong hands-on experience with Python for data processing and transformation
  • Strong experience with SQL and working with large-scale datasets
  • Proven experience in data validation, data transformation, and normalization

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 Journey Analytics datasets and downstream reporting

Key facts

Hard skills

Other skills

  • Detail Oriented
  • Communication

About the company

Blend360 logo

Blend360

Artificial Intelligence & Machine Learning Services

Our Vision is to build a company of world-class people that helps our clients optimize business performance through data, technology and analytics. Blend360 has two divisions: Data Science Solutions: We work at the intersection of data, technology and analytics. Talent Solutions: We live and breathe the digital and talent marketplace.

Company details

Company typeScaleup
IndustryArtificial Intelligence & Machine Learning Services
Company size501 - 1000

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Job description

Company Description

Blendβ€―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.comβ€― 

Job Description

uild, maintain, and optimize scalable data solutions to support Journey Analytics 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, 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 Journey Analytics 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.

Qualifications

Qualifications

  • Hands-on experience developing and maintaining data pipelines in Databricks.
  • Strong hands-on experience with Python for data processing and transformation.
  • Strong experience with SQL and working with large-scale datasets.
  • Proven experience in data validation, data transformation, and normalization.
  • Experience building and maintaining ETL pipelines and handling data ingestion workflows.
  • Strong attention to detail with a focus on data quality and reliability.
  • 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.

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.

Additional Information

Our Perks and Benefits: 

πŸ“š 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. 

πŸ›« Travel opportunities to attend industry conferences and meet clients. 

πŸ‘©β€πŸ« 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.  

βš–οΈ 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. 

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MR

Marcus Rivera

Chief Revenue Officer

m.rivera@company.com
linkedin.com/in/marcusrivera
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