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
Job DescriptionWe are looking for a skilled Data Engineer with 4+ years of experience to design, build, and maintain scalable data pipelines and platforms using Azure and Databricks. The ideal candidate will work closely with analytics, data science, and business teams to deliver reliable, high-performance data solutions that enable data-driven decision-making.
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
- Design, develop, and optimize end-to-end data pipelines using Azure Databricks
- 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.
- 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.
- 4+ years of experience in Data Engineering.
- Solid experience with Databricks.
- Strong experience working with GitHub repositories and version control workflows.
- Hands-on experience developing and maintaining data pipelines in Azure Databricks.
- Strong experience with SQL and large-scale data processing.
- Proven experience refactoring and maintaining legacy codebases.
- Hands-on experience with Apache Spark (PySpark preferred).
- Experience working with DBT for data transformation and modeling.
- Strong understanding and hands-on experience with Medallion Architecture (Bronze, Silver, Gold).
- 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.
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.
Skills Required
- 4+ years of experience in Data Engineering
- Experience with Azure
- Solid experience with Databricks
- Hands-on experience developing and maintaining data pipelines in Azure Databricks
- Strong experience working with GitHub repositories and version control workflows
- Strong experience with SQL and large-scale data processing
- Proven experience refactoring and maintaining legacy codebases
- Hands-on experience with Apache Spark
- PySpark
- Experience working with DBT for data transformation and modeling
- Strong understanding and hands-on experience with Medallion Architecture (Bronze, Silver, Gold)
- 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 with minimal supervision
Blend360 Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Blend360 and has not been reviewed or approved by Blend360.
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Fair & Transparent Compensation — Pay is considered fair-to-good by many, and public salary postings for common data roles indicate competitive packages in numerous markets. Feedback suggests overall company sentiment aligns with acceptable compensation relative to peers in consulting and analytics.
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Flexible Benefits — Flexible and remote/hybrid work arrangements are consistently highlighted in official materials and role descriptions. Feedback suggests flexibility is a meaningful part of the total rewards experience.
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Retirement Support — A 401(k) with company match is part of the core package. Feedback suggests retirement offerings are standard and contribute to a complete benefits set.
Blend360 Insights
What We Do
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.








