Manager Data Engineer - AWS Databricks

Bogotá, Bogota, Colombia

⚠️ We'll shut down after Aug 1st - try foo🦍 for all jobs in tech ⚠️

Blend360

Blend360 co-creates value with leading companies through the integration of data, advanced analytics, technology & people. Get in touch with us today.

View all jobs at Blend360

Apply now Apply later

Company Description

Blend360 is a world class marketing, analytics, and technology company that delivers the best results for our clients. Our primary focus is Data Sciences; leveraging data and applied mathematics to solve our clients’ business challenges. Blend360 is known for our exceptional people, our get-it-done mentality, and delivering high impact and sustainable results. If you love to solve difficult problems and deliver results; if you like to learn new things and apply innovative, state-of-the-art methodology, join us at Blend360.

Job Description

We are seeking a seasoned Data Engineering Manager with 8+ years of experience to lead and grow our data engineering capabilities. This role demands strong hands-on expertise in Python, SQL, Spark, and advanced proficiency in AWS and Databricks. As a technical leader, you will be responsible for architecting and optimizing scalable data solutions that enable analytics, data science, and business intelligence across the organization.

Key Responsibilities:

  • Lead the design, development, and optimization of scalable and secure data pipelines using AWS services such as Glue, S3, Lambda, EMR, and Databricks Notebooks, Jobs, and Workflows.
  • Oversee the development and maintenance of data lakes on AWS Databricks, ensuring performance and scalability.
  • Build and manage robust ETL/ELT workflows using Python and SQL, handling both structured and semi-structured data.
  • Implement distributed data processing solutions using Apache Spark/PySpark for large-scale data transformation.
  • Collaborate with cross-functional teams including data scientists, analysts, and product managers to ensure data is accurate, accessible, and well-structured.
  • Enforce best practices for data quality, governance, security, and compliance across the entire data ecosystem.
  • Monitor system performance, troubleshoot issues, and drive continuous improvements in data infrastructure.
  • Conduct code reviews, define coding standards, and promote engineering excellence across the team.
  • Mentor and guide junior data engineers, fostering a culture of technical growth and innovation.

Qualifications

Requirements

  • 8+ years of experience in data engineering with proven leadership in managing data projects and teams.
  • Expertise in Python, SQL, Spark (PySpark), and experience with AWS and Databricks in production environments.
  • Strong understanding of modern data architecture, distributed systems, and cloud-native solutions.
  • Excellent problem-solving, communication, and collaboration skills.
  • Prior experience mentoring team members and contributing to strategic technical decisions is highly desirable.

Additional Information

Our perks and benefits:  

⚖️ Flexible working options to help you strike the right balance.  

👨🏽‍💻 All the equipment you need to harness your talent (Macbook and accessories).  

🎮After office events, football, tennis and game nights (headquarters).  

📚 Learning opportunities:  

  • AWS Certifications (we are AWS Partners).  

  • Study plans, courses and other certifications.  

  • English Lessons.  

👩‍🏫 Mentoring and Development opportunities to shape your career path.  

🎁 Anniversary and birthday Perks  

🏡 Great location and even greater teammates!  

 

Apply now Apply later

* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰

Job stats:  0  0  0

Tags: Architecture AWS Business Intelligence Databricks Data pipelines Data quality Distributed Systems ELT Engineering ETL Lambda Mathematics Pipelines PySpark Python Security Spark SQL

Perks/benefits: Career development Flex hours Gear Startup environment Team events

Region: South America
Country: Colombia

More jobs like this