Lead Data Engineer

Role: Lead Data Engineer
Work Location: Role: Lead Data Engineer
Work Location: Phoenix, AZ – Local Only
Skills:
• Google Cloud Platform (GCP
• Hadoop
• HBase
• Kafka
• Redis
• Elasticsearch
• Map RDB or similar distributed data platforms
• Python development

Responsibilities
• Lead the design, implementation, and optimization of enterprise real-time and batch data platforms
• Provide technical leadership and mentorship to data engineering teams supporting large-scale data ecosystems
• Drive modernization efforts leveraging Google Cloud Platform (GCP) technologies
• Design and support scalable data pipelines for ingestion, processing, storage, and analytics
• Collaborate with architecture, infrastructure, security, and analytics teams to deliver enterprise data solutions
• Support and optimize distributed data platforms including streaming, search, caching, and data processing technologies
• Develop automation, monitoring, and operational processes to improve platform reliability and performance
• Partner with stakeholders to define platform roadmaps and future-state architecture strategies
• Evaluate emerging technologies and support AI, machine learning, and GenAI-related initiatives
• Establish engineering best practices for scalability, performance, security, and operational excellence

Required Qualifications
• 10+ years of experience in data engineering, platform engineering, or big data environments
• 8+ years of experience leading teams supporting enterprise-scale batch and real-time data platforms
• Strong hands-on experience with:
o Hadoop
o HBase
o Kafka
o Redis
o Elasticsearch
o MapRDB or similar distributed data platforms
• 3+ years of experience with Google Cloud Platform (GCP), including:
o Bigtable
o Dataproc
o Pub/Sub
o Composer
• Strong Python development experience
• Experience designing and supporting large-scale distributed systems and real-time data architectures
• Proven ability to lead technical initiatives and mentor engineering teams
• Strong analytical, troubleshooting, and communication skills

Preferred Qualifications
• Experience supporting AI, machine learning, or Generative AI initiatives
• GenAI certifications or related technical training
• Experience with enterprise observability and monitoring platforms, including ELK Stack
• Familiarity with cloud-native architecture and platform engineering best practices
• Experience supporting highly available, mission-critical production environments
• Knowledge of infrastructure automation and DevOps methodologies

What We’re Looking For
• Strong technical leader with a passion for modern data platforms and cloud technologies
• Ability to drive strategic platform initiatives while remaining hands-on when needed
• Experience leading cross-functional teams in complex enterprise environments
• Strong communication skills and ability to influence technical direction
• Commitment to innovation, operational excellence, and continuous improvement
– Local Only
Skills:
• Google Cloud Platform (GCP
• Hadoop
• HBase
• Kafka
• Redis
• Elasticsearch
• Map RDB or similar distributed data platforms
• Python development

Responsibilities
• Lead the design, implementation, and optimization of enterprise real-time and batch data platforms
• Provide technical leadership and mentorship to data engineering teams supporting large-scale data ecosystems
• Drive modernization efforts leveraging Google Cloud Platform (GCP) technologies
• Design and support scalable data pipelines for ingestion, processing, storage, and analytics
• Collaborate with architecture, infrastructure, security, and analytics teams to deliver enterprise data solutions
• Support and optimize distributed data platforms including streaming, search, caching, and data processing technologies
• Develop automation, monitoring, and operational processes to improve platform reliability and performance
• Partner with stakeholders to define platform roadmaps and future-state architecture strategies
• Evaluate emerging technologies and support AI, machine learning, and GenAI-related initiatives
• Establish engineering best practices for scalability, performance, security, and operational excellence

Required Qualifications
• 10+ years of experience in data engineering, platform engineering, or big data environments
• 8+ years of experience leading teams supporting enterprise-scale batch and real-time data platforms
• Strong hands-on experience with:
o Hadoop
o HBase
o Kafka
o Redis
o Elasticsearch
o MapRDB or similar distributed data platforms
• 3+ years of experience with Google Cloud Platform (GCP), including:
o Bigtable
o Dataproc
o Pub/Sub
o Composer
• Strong Python development experience
• Experience designing and supporting large-scale distributed systems and real-time data architectures
• Proven ability to lead technical initiatives and mentor engineering teams
• Strong analytical, troubleshooting, and communication skills

Preferred Qualifications
• Experience supporting AI, machine learning, or Generative AI initiatives
• GenAI certifications or related technical training
• Experience with enterprise observability and monitoring platforms, including ELK Stack
• Familiarity with cloud-native architecture and platform engineering best practices
• Experience supporting highly available, mission-critical production environments
• Knowledge of infrastructure automation and DevOps methodologies

What We’re Looking For
• Strong technical leader with a passion for modern data platforms and cloud technologies
• Ability to drive strategic platform initiatives while remaining hands-on when needed
• Experience leading cross-functional teams in complex enterprise environments
• Strong communication skills and ability to influence technical direction
• Commitment to innovation, operational excellence, and continuous improvement