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.
