Crocs
What You'll Do
Team Leadership
Manage, mentor, and grow a high-performing team of data engineers. Provide technical direction, career development support, and day-to-day coaching. Technical Ownership
Oversee design, implementation, and maintenance of scalable data pipelines, data models, and orchestration frameworks. Architecture & Standards
Drive adoption of modern data engineering practices, including modular data modeling, CI/CD pipelines, test automation, and performance optimization. Project Delivery
Ensure timely and reliable delivery of data engineering projects while balancing long-term platform stability and scalability. Operational Excellence
Proactively identify and resolve issues related to data integrity, data quality, and system performance. Champion automation and monitoring practices. Documentation & Governance
Promote strong documentation standards and contribute to data governance and compliance initiatives. Cross-Functional Collaboration
Work closely with analytics, data science, business intelligence, and IT teams to align technical solutions with business needs. Continuous Improvement
Encourage a culture of learning by staying current with advancements in the data ecosystem and exploring emerging technologies in AI/ML, streaming, and real-time data processing. Data Modeling
Design, implement, and maintain scalable data models that support the Enterprise Data Warehouse (EDW) and analytical workloads following best practices and restrictions imposed by respective technologies. ETL/ELT
Design and implement efficient, scalable and easy-to-manage data movement processes supporting both batch and near-real-time data streams. CI/CD
Automate code integration, testing, and deployment using Git to ensure fast, reliable, and consistent delivery of data pipelines and ETL code. What You'll Bring to the Table
Bachelors degree or equivalent experience in computer science, information technology, engineering, mathematics, or equivalent technical degree. 8+ years in Data Engineering roles, with 2+ years in management capacity. 4+ years of direct development in Snowflake, Snowflake certifications preferred. Strong proficiency in Python, PySpark, and Apache Airflow. Experience utilizing Git version control in a data environment, working with/in GitHub, GitActions. Experience designing data models following Kimball Dimensional Modeling best practices. Experience working with modern ETL/ELT tools, such as Databricks. Prior experience working in a cloud platform (Azure preferred). Experience with a business intelligence tool, ideally Power BI, preferred. Experience working with Azure Data Factory, preferred. The Company is an Equal Opportunity Employer committed to a diverse and inclusive work environment. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, or disability, or any other protected classification. #J-18808-Ljbffr
Team Leadership
Manage, mentor, and grow a high-performing team of data engineers. Provide technical direction, career development support, and day-to-day coaching. Technical Ownership
Oversee design, implementation, and maintenance of scalable data pipelines, data models, and orchestration frameworks. Architecture & Standards
Drive adoption of modern data engineering practices, including modular data modeling, CI/CD pipelines, test automation, and performance optimization. Project Delivery
Ensure timely and reliable delivery of data engineering projects while balancing long-term platform stability and scalability. Operational Excellence
Proactively identify and resolve issues related to data integrity, data quality, and system performance. Champion automation and monitoring practices. Documentation & Governance
Promote strong documentation standards and contribute to data governance and compliance initiatives. Cross-Functional Collaboration
Work closely with analytics, data science, business intelligence, and IT teams to align technical solutions with business needs. Continuous Improvement
Encourage a culture of learning by staying current with advancements in the data ecosystem and exploring emerging technologies in AI/ML, streaming, and real-time data processing. Data Modeling
Design, implement, and maintain scalable data models that support the Enterprise Data Warehouse (EDW) and analytical workloads following best practices and restrictions imposed by respective technologies. ETL/ELT
Design and implement efficient, scalable and easy-to-manage data movement processes supporting both batch and near-real-time data streams. CI/CD
Automate code integration, testing, and deployment using Git to ensure fast, reliable, and consistent delivery of data pipelines and ETL code. What You'll Bring to the Table
Bachelors degree or equivalent experience in computer science, information technology, engineering, mathematics, or equivalent technical degree. 8+ years in Data Engineering roles, with 2+ years in management capacity. 4+ years of direct development in Snowflake, Snowflake certifications preferred. Strong proficiency in Python, PySpark, and Apache Airflow. Experience utilizing Git version control in a data environment, working with/in GitHub, GitActions. Experience designing data models following Kimball Dimensional Modeling best practices. Experience working with modern ETL/ELT tools, such as Databricks. Prior experience working in a cloud platform (Azure preferred). Experience with a business intelligence tool, ideally Power BI, preferred. Experience working with Azure Data Factory, preferred. The Company is an Equal Opportunity Employer committed to a diverse and inclusive work environment. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, or disability, or any other protected classification. #J-18808-Ljbffr