Associate Director - Data Engineering

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 highly skilled and experienced Associate Director of Data Engineering to lead our data engineering team and support our data science and business intelligence teams. The Engineering Director will build and manage a high-performance team of Data Engineers and will foster a data-driven culture across the organization. The Director of Data Engineering will be responsible for developing and implementing strategies for data collection, storage, processing, and analysis to meet the needs of the organization. This role will require a strong understanding of data engineering, data management, and data analytics technologies and techniques. 

Responsibilities: 

• Lead the development and implementation of data engineering strategies to support data science and business intelligence teams. 

• Oversee the design, development, and maintenance of our data infrastructure, including data pipelines, data warehousing, and data integration solutions. 

• Collaborate with data scientists and business intelligence teams to ensure that data is collected, stored, processed, and analyzed in a way that meets their needs. 

• Ensure that our data is accurate, reliable, and secure. 

• Ensure that the team designs, develops, and delivers high-quality, performant, scalable, well-tested, documented, and sensible technical solutions suitable to high-impact technical challenges  

• Develop and implement best practices for data management, data governance, and data quality. 

• Manage and mentor a team of data engineers and data architects. 

• Stay up-to-date with the latest data engineering, data management, and data analytics technologies and techniques. 

• Work closely with other departments to identify data-related opportunities and challenges and develop solutions to address them. 

Qualifications

• Bachelor's or Master's degree in Computer Science, Engineering, or a related field. 

• 10+ years of experience in data engineering, data management, or a related field. 

• 5+ years of experience in managing data engineering teams 

• Experience managing and leading a team of data engineers and data architects. 

• Strong knowledge of data engineering and data management technologies, such as Hadoop, Spark, SQL, NoSQL, and ETL tools. 

• Experience developing efficient and scalable production software in Python or Scala, or other programming languages commonly used in data engineering  

• Understanding of event-driven and/or streaming workflows with tools like Kafka and Spark  

• Aptitude with ETL concepts and tools, including experience ingesting, processing, and transforming a variety of data at scale  

• Proficiency with SQL and NoSQL databases, data warehousing concepts, and cloud-based analytics databases (Snowflake)  

• Experience with infrastructure tools like Kubernetes, CloudFormation, Terraform etc.  

• Demonstrated ability as a strategic technical partner, working collaboratively with data analytics, data science, product, business intelligence, and other cross-functional partners, to plan, prioritize, and achieve company goals  

• Experience developing and nurturing data engineering talent, including implementing training, upskilling, and mentorship plans  

• Expert-level engineering, architecture, and system design knowledge, with strong computer science fundamentals  

• Experience designing and implementing data warehousing and data integration solutions. 

• Strong understanding of data governance, data quality, and data security best practices. 

• Experience working with data science and business intelligence teams. 

• Strong leadership skills with the ability to motivate and manage teams 

• Excellent communication and collaboration skills. 

• Strong problem-solving skills and attention to detail.