Overview
On Site
USD 241,400.00 - 358,600.00 per year
Full Time
Skills
NetApp
Strategic Leadership
Roadmaps
Decision-making
Emerging Technologies
Investments
Optimization
ELT
Data Quality
Reporting
Use Cases
Customer Facing
Performance Tuning
Collaboration
Product Engineering
Team Building
Training And Development
Mentorship
Accountability
Innovation
Continuous Improvement
Coaching
Advanced Analytics
Artificial Intelligence
Generative Artificial Intelligence (AI)
Machine Learning (ML)
Data Governance
Access Control
Computer Science
Data Engineering
Management
SQL
Data Modeling
Cloud Computing
Amazon Web Services
Microsoft Azure
Google Cloud Platform
Google Cloud
Big Data
Apache Hadoop
Apache Spark
Extract
Transform
Load
Orchestration
Data Warehouse
Snow Flake Schema
Amazon Redshift
Real-time
Data Processing
Streaming
Apache Kafka
Conflict Resolution
Problem Solving
Attention To Detail
SaaS
Communication
Strategic Thinking
Stakeholder Management
Health Insurance
Life Insurance
Recruiting
Job Details
Job Summary
NetApp is seeking a visionary and strategic Director of Data Engineering to lead the data engineering function within the Keystone business unit. This leader will be responsible for shaping and executing the data engineering strategy that powers our customer-facing services, ensures platform reliability, and drives business-critical insights through scalable, real-time data solutions. The ideal candidate will be a seasoned leader who combines deep technical expertise with proven success in managing high-performing teams and aligning data infrastructure with company goals
Job Responsibilities
Key Responsibilities:
Strategic Leadership & Vision:
Define and lead the data engineering roadmap aligned with Keystone's business and technology objectives.
Champion data-driven decision making across Keystone by evangelizing best practices in data engineering, governance, and infrastructure.
Identify emerging technologies and trends to inform strategic investments and innovation.
Data Infrastructure & Architecture Oversight:
Guide the design and evolution of scalable, secure, and highly available data platforms and real-time processing pipelines.
Oversee the development and optimization of ETL/ELT processes, data models, and data quality frameworks.
Ensure architecture supports both operational reporting and advanced analytics use cases.
Operational Reliability & Performance:
Own the performance, uptime, and resilience of all data systems supporting customer-facing services.
Implement monitoring, alerting, and proactive performance tuning for mission-critical data platforms.
Cross-Functional Collaboration:
Collaborate with product, engineering, AI, and business teams to ensure data platforms support the full Keystone lifecycle.
Partner with key stakeholders to deliver end-to-end solutions.
Team Building & People Development:
Build, mentor, and retain a high-performing team of data engineers, business analysts, and architects.
Promote a culture of accountability, innovation, and continuous improvement within the team.
Provide guidance and coaching on architectural best practices and scalable data engineering solutions.
Advanced Analytics & Automation Enablement:
Support the Keystone Data Insights and AI teams in deploying GenAI and ML capabilities.
Drive the implementation of automation and self-service data tools for internal stakeholders.
Governance & Source of Truth Ownership:
Establish and enforce data governance policies, including lineage, access control, and cataloging.
Ensure a consistent, unified source of truth for all critical business metrics and operational data views.
Job Requirements
Bachelor's or Master's degree in Computer Science, Engineering, or a related technical field.
10+ years of experience in data engineering, including 4+ years managing high performing teams.
Strong proficiency in SQL and experience with data modeling.
Experience with cloud platforms (e.g., AWS, Azure, Google Cloud Platform) and big data technologies (e.g., Hadoop, Spark).
Familiarity with ETL tools and data pipeline orchestration (e.g., Airflow).
Knowledge of data warehousing solutions (e.g., Snowflake, Redshift).
Experience with real-time data processing and streaming platforms (e.g., Kafka).
Strong problem-solving skills and attention to detail.
Strong understanding of SaaS or data-as-a-service business models.
Excellent communication, strategic thinking, and executive stakeholder management skills.
Compensation:
The target salary range for this position is 241,400 - 358,600 USD. The salary offered will be determined by the candidate's location, qualifications, experience, and education and may be outside of this range. Final compensation packages are competitive and in line with industry standards, reflecting a variety of factors, and include a comprehensive benefits package. This may cover Health Insurance, Life Insurance, Retirement or Pension Plans, Paid Time Off (PTO), various Leave options, Performance-Based Incentives, employee stock purchase plan, and/or restricted stocks (RSU's), with all offerings subject to regional variations and governed by local laws, regulations, and company policies. Benefits may vary by country and region, and further details will be provided as part of the recruitment process.
NetApp is seeking a visionary and strategic Director of Data Engineering to lead the data engineering function within the Keystone business unit. This leader will be responsible for shaping and executing the data engineering strategy that powers our customer-facing services, ensures platform reliability, and drives business-critical insights through scalable, real-time data solutions. The ideal candidate will be a seasoned leader who combines deep technical expertise with proven success in managing high-performing teams and aligning data infrastructure with company goals
Job Responsibilities
Key Responsibilities:
Strategic Leadership & Vision:
Define and lead the data engineering roadmap aligned with Keystone's business and technology objectives.
Champion data-driven decision making across Keystone by evangelizing best practices in data engineering, governance, and infrastructure.
Identify emerging technologies and trends to inform strategic investments and innovation.
Data Infrastructure & Architecture Oversight:
Guide the design and evolution of scalable, secure, and highly available data platforms and real-time processing pipelines.
Oversee the development and optimization of ETL/ELT processes, data models, and data quality frameworks.
Ensure architecture supports both operational reporting and advanced analytics use cases.
Operational Reliability & Performance:
Own the performance, uptime, and resilience of all data systems supporting customer-facing services.
Implement monitoring, alerting, and proactive performance tuning for mission-critical data platforms.
Cross-Functional Collaboration:
Collaborate with product, engineering, AI, and business teams to ensure data platforms support the full Keystone lifecycle.
Partner with key stakeholders to deliver end-to-end solutions.
Team Building & People Development:
Build, mentor, and retain a high-performing team of data engineers, business analysts, and architects.
Promote a culture of accountability, innovation, and continuous improvement within the team.
Provide guidance and coaching on architectural best practices and scalable data engineering solutions.
Advanced Analytics & Automation Enablement:
Support the Keystone Data Insights and AI teams in deploying GenAI and ML capabilities.
Drive the implementation of automation and self-service data tools for internal stakeholders.
Governance & Source of Truth Ownership:
Establish and enforce data governance policies, including lineage, access control, and cataloging.
Ensure a consistent, unified source of truth for all critical business metrics and operational data views.
Job Requirements
Bachelor's or Master's degree in Computer Science, Engineering, or a related technical field.
10+ years of experience in data engineering, including 4+ years managing high performing teams.
Strong proficiency in SQL and experience with data modeling.
Experience with cloud platforms (e.g., AWS, Azure, Google Cloud Platform) and big data technologies (e.g., Hadoop, Spark).
Familiarity with ETL tools and data pipeline orchestration (e.g., Airflow).
Knowledge of data warehousing solutions (e.g., Snowflake, Redshift).
Experience with real-time data processing and streaming platforms (e.g., Kafka).
Strong problem-solving skills and attention to detail.
Strong understanding of SaaS or data-as-a-service business models.
Excellent communication, strategic thinking, and executive stakeholder management skills.
Compensation:
The target salary range for this position is 241,400 - 358,600 USD. The salary offered will be determined by the candidate's location, qualifications, experience, and education and may be outside of this range. Final compensation packages are competitive and in line with industry standards, reflecting a variety of factors, and include a comprehensive benefits package. This may cover Health Insurance, Life Insurance, Retirement or Pension Plans, Paid Time Off (PTO), various Leave options, Performance-Based Incentives, employee stock purchase plan, and/or restricted stocks (RSU's), with all offerings subject to regional variations and governed by local laws, regulations, and company policies. Benefits may vary by country and region, and further details will be provided as part of the recruitment process.
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.