Company 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 Job Description As a Lead Data Engineer, your role is to spearhead the data engineering teams and elevate the team to the next level You will be responsible for laying out the architecture of the new project as well as selecting the tech stack associated with it. You will plan out the development cycles deploying AGILE if possible and create the foundations for good data stewardship with our new data products You will also set up a solid code framework that needs to be built to purpose yet have enough flexibility to adapt to new business use cases tough but rewarding challenge Responsibilities - Lead and Migrate legacy data infrastructure while ensuring performance, security, and scalability. - Build and optimize data systems, pipelines, and analytical tools, leveraging a bronze-silver-gold architecture. - Develop and configure Databricks notebooks and pipelines for ingestion of data from both on-premise and cloud environments, following native Databricks standards. - Collaborate with stakeholders to translate business needs into robust data solutions, and effectively communicate technical progress, risks, and recommendations. - Implement strong data governance and access control mechanisms to ensure data quality, security, and compliance. - Conduct advanced data analysis to support decision-making and reporting needs. - Apply QA testing practices within data workflows, particularly in healthcare environments. - Drive initiatives in Data Discovery, Data Lineage, and Data Quality across the organization. Qualifications - Bachelor´s degree in computer science, Engineering, or a related field. - 5+ years of hands-on experience in data engineering, with at least 2 years working with Azure or Databricks - Experience working with Azure Cloud, CI/CD pipelines, and Agile methodologies - Proficiency in developing and managing Databricks notebooks and implementing data engineering frameworks. - Strong programming skills in Python for data processing and automation. - Advanced proficiency in SQL for querying and transforming large datasets. - Solid understanding of data modelling, warehousing, and performance optimization techniques. - Proven experience in data cataloging and inventorying large-scale datasets. - Pyspark experience would be a plus - Strong ability to work independently and a desire to lead and mentor junior Data Engineers. Additional Information 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. 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.