Data Engineering Manager

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The Data Engineering Manager will lead distributed teams responsible for designing, modernizing, and operating large-scale data pipelines on the Nexus One platform — an open-source-based data and AI control plane for regulated enterprise environments. This leader combines hands-on technical depth with strategic delivery management, ensuring that complex data workloads are refactored, migrated, and optimized using modern, composable frameworks. The role requires strong architectural intuition, proven leadership, and fluency in modern data-engineering technologies.

• Lead distributed data engineering teams to design, modernize, and operate large-scale data pipelines on Nexus One.
• Guide architecture and implementation of open-source data stack components and data governance practices.
• Drive migration and modernization programs with a focus on performance, reliability, and cost efficiency.
• Partner with stakeholders to translate executive vision into technical execution and measurable outcomes.
• Foster a culture of delivery excellence in Agile/Dev Ops settings.

• Distributed Data Systems:
  Apache Spark (core, SQL, streaming) and Airflow orchestration.
• Open-Source Data Stack:
  Iceberg, Trino/Presto, Hive, NiFi, Kafka.
• Data Modeling & Transformation: SQL, DBT, and schema-on-read design principles.
• Programming & Scripting:
  Python, Scala, and Java for data pipelines.
• Infrastructure & Automation:
  Kubernetes, Terraform, Helm, Git Lab CI/Jenkins, Linux-based environments.
• Governance & Security:
  Ranger, Data Hub, RBAC, and enterprise IAM/SSO integration.
• Data Quality & Testing:
  Great Expectations or similar validation frameworks.
• Delivery Leadership:
  Experience managing distributed engineering teams in Agile/Dev Ops settings.

• 8–12 years in data engineering or platform modernization, including 3+ years leading technical teams.
• Strong foundation in open-source and hybrid-cloud data ecosystems.
• Demonstrated success leading migration or modernization programs at enterprise scale.
• Excellent communication and stakeholder-management skills; capable of bridging executive vision and technical execution.

• Delivery of high-performing, production-ready data pipelines on the Nexus One platform.
• Adherence to governance, quality, and performance SLAs.
• Adoption of standardized frameworks and automation across engineering teams.
• Measurable improvement in pipeline reliability, cost efficiency, and developer productivity.
• High engagement, retention, and growth within the data-engineering team.

• Must-Have Core
  
  Skills:
  
  Distributed Data Systems, Open-Source Data Stack, Data Modeling & Transformation, Programming & Scripting, Infrastructure & Automation, Governance & Security, Data Quality & Testing, Delivery Leadership.

Seniority level:
Mid-Senior level

Employment type:

Full-time

Job function:
Engineering and Information Technology

Industries: IT Services and IT Consulting

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