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 www.blend360.com
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.
