Lead Data Engineer

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

We’re looking for a Lead Data Engineer with strong experience designing, developing, and maintaining enterprise data solutions. This role will be responsible for the design, structure, integration, and maintenance of data across data warehouses, operational data stores, and other enterprise data infrastructures.

The ideal candidate combines strong technical expertise in SQL, data engineering, ETL, data integration, and data architecture with strong analytical and problem-solving skills. This person will work closely with technical and business stakeholders to design reliable data solutions, optimize high-volume workloads, and ensure data is accurate, accessible, and fit for business needs.

Responsibilities

Own the middle layer of the data pipeline, combining Quantum interaction data with account, device, and other operational data sources.; Build and maintain ETL workflows that transform data on daily, weekly, and monthly schedules.; Develop and manage AWS processing resources, validate outputs, and prepare reliable datasets for Tableau.; Design and maintain application data structures that minimize compute requirements and support efficient dashboard performance.; Investigate data discrepancies, troubleshoot pipeline issues, and adapt workflows as application features and reporting needs evolve.; Collaborate with the engineering lead, fellow data engineers, application developers, and data product owners as pipelines grow in complexity.

Requirements

+ 5 years of experience in Data Engineering, Data Architecture, or a related field.; Strong hands-on AWS experience, including managing resources for data processing.; Proficiency in SQL and experience with Spark.; Experience building ETL pipelines, integrating multiple data sources, and organizing data for analytics.; An investigative mindset and the ability to independently work through ambiguous technical problems.; A collaborative approach, with the ability to take ownership of assigned work within an established team.; Advanced English (B2+)

Benefits

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.; Career development plans and mentorship programs to help shape your path.; Special day rewards to celebrate birthdays, work anniversaries, and other personal milestones.; Company-provided equipment.