Principal Engineer – Device Analytics

Jobtailor; New Jersey; On-site; USD 130,000 - 190,000; Full time

Job summary

Jobtailor seeks a senior data engineer to design and implement scalable data applications on big data platforms. You will architect secure on-premises data processing and lead integration across diverse sources. Experience with Kafka streaming and Linux-based Apache ecosystems is essential.

You will guide QA, collaborate with cross-functional teams, and mentor peers while aligning with security and governance standards. A strong background in distributed data architectures is needed.

Qualifications

• Bachelor’s degree or four or more years of work experience.
• Six or more years of relevant experience, demonstrated through work and/or military experience or specialized training.
• Experience designing and implementing production data applications using Java, Python, or Scala on big data platforms.
• Deep expertise in big data technologies and data optimization techniques.
• Experience with streaming technologies, specifically Kafka.
• Experience with open-source software platforms, such as the Apache ecosystem and Linux.
• Master’s degree or PhD in Computer Science, Computer Engineering, Software Engineering, Data Science, or a related quantitative field (even better).
• Ability to optimize data flow and design efficient, scalable data pipelines, including data lakes and warehouses on containerized clusters.
• Strong understanding of distributed data architecture concepts, such as caching, MapReduce, and stream processing.
• Knowledge of data security, governance, and compliance.
• Proficiency in Java, Python, Scala, and SQL.
• Strong analytical capabilities, creativity, and critical thinking skills.
• Effective written and verbal communication and ability to facilitate team collaboration.

Responsibilities

• Design and build production data applications using Java, Python, or Scala on big data platforms.
• Architect secure on-premises data processing and data engineering solutions.
• Lead data integration strategies from multiple sources and ensure compliance.
• Oversee testing and quality assurance for enterprise initiatives.
• Mentor colleagues and communicate complex tech to non-technical audiences.

Skills

Big Data Technologies

Data Pipeline Optimization

Java Programming

Kafka Streaming

Data Security Compliance

Data Governance

SQL

Data Integration Strategies

Education

Bachelor's Degree

Master's Degree

PhD in Computer Science

Tools

Apache Ecosystem

Linux

Containerized Clusters

On-Premises Infrastructure

Data Engineering Solutions

Data Lakes

Data Warehouses

MapReduce

Job description

• Design, create, and maintain solutions for connected devices and new form factors
• Build clients for device data collection and provide insights from device data
• Build iOS and Android clients to collect device performance insights
• Build required on-premises infrastructure to process device data and generate insights
• Architect secure on-premises data processing and data engineering solutions
• Maintain on-premises hardware configurations compliant with Verizon security requirements
• Architect and lead comprehensive data integration strategies from multiple sources
• Perform performance tuning and diagnose and resolve complex big data and streaming issues
• Develop and deploy high-capacity data processing, database architecture, and network security solutions
• Oversee integration testing and guide quality assurance teams on enterprise initiatives
• Lead requirements gathering, project scoping, system engineering, and validation lifecycle activities
• Track evolving artificial intelligence and big data analytics methodologies and trends
• Assess and integrate external libraries and software frameworks
• Cultivate technical partnerships with Verizon internal groups and external OEMs
• Convey technical information to non-technical audiences and mentor colleagues

Requirements

• Bachelor’s degree or four or more years of work experience
• Six or more years of relevant experience, demonstrated through work and/or military experience or specialized training
• Experience designing and implementing production data applications using Java, Python, or Scala on big data platforms
• Deep expertise in big data technologies and data optimization techniques
• Experience with streaming technologies, specifically Kafka
• Experience with open-source software platforms, such as the Apache ecosystem and Linux
• Master’s degree or PhD in Computer Science, Computer Engineering, Software Engineering, Data Science, or a related quantitative field (even better)
• Ability to optimize data flow and design efficient, scalable data pipelines, including data lakes and warehouses on containerized clusters
• Strong understanding of distributed data architecture concepts, such as caching, MapReduce, and stream processing
• Knowledge of data security, governance, and compliance
• Proficiency in Java, Python, Scala, and SQL
• Strong analytical capabilities, creativity, and critical thinking skills
• Effective written and verbal communication and ability to facilitate team collaboration

Core Competencies

Demonstrates expertise in designing and implementing scalable data applications using Java, Python, and Scala, with a strong focus on big data technologies and data optimization. Proficient in architecting secure data processing solutions and integrating diverse data sources while ensuring compliance with security standards.

Highest-signal resume keywords

• Big Data Technologies
• Data Pipeline Optimization
• Java Programming
• Kafka Streaming
• Data Security Compliance

Hard Skills

• Java
• Python
• Scala
• SQL
• Big Data Platforms
• Data Optimization Techniques
• Data Lakes
• Data Warehouses
• MapReduce
• Stream Processing

Soft Skills

• Analytical Capabilities
• Creativity
• Critical Thinking
• Effective Communication
• Team Collaboration

Certifications & Qualifications

• Bachelor's Degree
• Master's Degree
• PhD in Computer Science

Industry Keywords

• Data Integration Strategies
• Data Governance
• Compliance Standards
• Performance Tuning
• Quality Assurance

Tools & Technologies

• Apache Ecosystem
• Linux
• Containerized Clusters
• On-Premises Infrastructure
• Data Engineering Solutions