Senior Data Engineer - Data Platform & Martech Engineering
Gen Digital1 month ago
Base Salary
$165k - $187k/yr
Responsibilities
- Design, build, and optimize scalable batch and streaming data platforms, ETL/ELT frameworks, and AI-ready data pipelines with emphasis on reliability, observability, scalability, and cost optimization.
- Architect and maintain enterprise-grade dimensional data models and semantic layers using Kimball methodologies, including fact and dimension design, conformed dimensions, slowly changing dimensions, star schemas, and governed business metrics.
- Translate business processes into scalable data contracts, integration patterns, and trusted analytical models supporting attribution, audience intelligence, experimentation, personalization, and data activation.
- Design and support martech and customer data infrastructure for audience orchestration, customer journey automation, reverse ETL, and real-time marketing use cases.
- Build and operationalize AI-powered solutions, intelligent agents, and data products that improve productivity, customer engagement, campaign optimization, and data access.
- Define and enforce standards for schema evolution, data lineage, governance, metric consistency, access controls, naming conventions, and data quality SLAs.
- Improve operational excellence through monitoring, alerting, freshness validation, schema drift detection, incident response, root cause analysis, and production support.
- Lead technical design discussions and architecture reviews, mentor teammates, and promote AI-assisted engineering practices.
Requirements
- Bachelor’s degree in Computer Science, Engineering, Information Systems, Mathematics, or a related technical field is required; a master’s degree is preferred.
- At least 5 years of experience designing, building, and operating production-grade data platforms and distributed data systems.
- Strong experience developing scalable data products, semantic layers, and analytical data models for enterprise reporting and activation use cases.
- Expertise in dimensional data modeling and Kimball methodologies, including fact and dimension modeling, conformed dimensions, slowly changing dimensions, and metric governance.
- Experience with customer data platforms, marketing technology ecosystems, or data activation platforms is highly preferred.
- Ability to write technical design documents, evaluate architectural trade-offs, and deliver scalable engineering solutions.
- Experience in fintech, financial services, adtech, or other highly regulated industries is preferred.
- Expert SQL skills and strong proficiency in Python, Spark, or Java for scalable, maintainable, testable production code.
- Hands-on experience with cloud data platforms, orchestration and transformation frameworks, streaming and event-driven architectures, martech platforms, and enterprise data quality practices.
- Experience implementing monitoring, SLA management, freshness validation, schema drift detection, and operational support processes.
- Familiarity with AI-assisted development tools and engineering productivity platforms.
- Strong communication, stakeholder management, collaboration, ownership, mentoring, and systems-thinking abilities.
Benefits
- Flexible working options, time off, competitive benefits, and well-being programs are offered.
- The role includes collaboration with cross-functional teams and opportunities for technical leadership, mentoring, and career growth.
Tech Stack
Amazon RedshiftApache AirflowApache KafkaApache SparkDatabricksdbtGoogle BigQueryJavaPythonSnowflakeSQL
Categories
Data Engineering
About Gen Digital
Gen Digital is a public consumer cyber safety company that sells subscription software and services for cybersecurity, online privacy, and identity protection under brands including Norton, Avast, LifeLock, Avira, AVG, CCleaner, and ReputationDefender. Formed in 2022 by the merger of NortonLifeLock and Avast, it is headquartered in Tempe, Arizona, and serves more than 150 countries with a user base approaching 500 million. Revenue comes primarily from direct-to-consumer subscriptions and partnerships.