Associate Director - Data Engineering

What you'll be doing

• 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.

What do we need from you

• 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.