Director, Data Engineering (Remote)

Posted 8 days agoViewed

💎 Seniority level: Director, 10+ years

📍 Location: United States, AZ, CA, CO, CT, FL, GA, ID, IL, IN, KS, MA, MD, ME, MI, MN, MO, NC, NH, NJ, NV, NY, OH, OK, OR, PA, SC, TN, TX, UT, VA, WA, WI, Washington D.C.

💸 Salary: 220000.0 - 250000.0 USD per year

🔍 Industry: Software Development

🏢 Company: Guild👥 1001-5000💰 $264,674,905 Series F over 2 years ago🫂 Last layoff 9 months agoEducation EdTech Career Planning

🗣️ Languages: English

⏳ Experience: 10+ years

🪄 Skills: AWSSQLCloud ComputingETLGCPMachine LearningSnowflakeAzureData engineeringData modeling

Requirements:

At least 10+ years of experience in data engineering, data warehousing, and/or business intelligence roles
Experience scaling and managing 10+ person teams
Highly focused on delivering results for internal and external stakeholders
Strong familiarity with cloud native (AWS/GCP/Azure) distributed computing and data storage mechanisms with hands-on experience in managing data infrastructure
Experience building alongside product and engineering teams utilizing cloud native technologies
Track record of delivering scalable and innovative solutions, leveraging cutting-edge technologies for data warehousing and machine learning such as DBT and DataBricks
Excellent leadership and communication skills with ability to influence and collaborate with stakeholders and peers
Strong technical proficiency enabling you to dig in as both a player and a coach
Experience managing and utilizing technologies such as Snowflake, DBT, DataBricks, etc to solve problems

Responsibilities:

Be responsible for roadmapping and implementing a vision for a scalable data platform
Establish best practices that achieve operational excellence in data availability, quality, and privacy
Partner with product and analytics teams to understand their data needs and translate their business requirements to scalable technical solutions
Collaborate with the applied science, analytics, and product teams to deliver high-impact data assets
Design and implement data pipelines and transformation workflows that are optimized for flexibility and data quality, leveraging best-in-class tools for transformation, observability, and testing
Lead, mentor, and scale the data engineering team, cultivating a culture of innovation, learning, and excellence.
Stay on top of industry trends, emerging technologies, and best practices for data processing, storage, compute and ML development
Develop and maintain robust governance frameworks, ensuring processes for monitoring, observability, and testing are in place to safeguard the integrity and availability of data

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