Senior Principal Data Platform Software Engineer
Atlassian
Senior Principal Data Platform Software Engineer
Job Description
Senior Principal Data Platform Software Engineer
š Job Overview
The Senior Principal Data Platform Software Engineer at Atlassian will lead the design and operation of data platform capabilities that support product analytics and ML experiences. This role involves driving the evolution of high-performance analytical databases and ensuring the reliability and strategic direction of Atlassian's product data platform. The position offers the opportunity to influence data platform strategy and shape how product data is managed at scale.
š Location: Multiple Locations, Global
š¢ Category: Engineering
š Posted: 2025-12-11 06:36 PM
šÆ Key Responsibilities
- Design, develop and own delivery of high quality big data and analytical platform solutions
- Improve and operate large-scale distributed data systems in the cloud (primarily AWS, with increasing integration with GCP and Kubernetes-based microservices)
- Drive the evolution of high-performance analytical databases and its integrations with products, cloud infrastructures (AWS and GCP) and isolated cloud environments
- Help define and uplift engineering and operational standards for petabyte scale data platforms
- Partner across multiple product and platform teams to deliver company-wide initiatives
- Act as a technical mentor and multiplier, raising the bar on design quality, code quality, and operational excellence
- Design and implement self-healing, resilient data platforms with strong observability, fault tolerance, and recovery characteristics
- Own the long-term architecture and technical direction of Atlassianās product data platform
- Be accountable for the reliability, cost efficiency, and strategic direction of Atlassianās product analytical data platform
- Partner with executives and influence senior leaders to align engineering efforts with Atlassianās long-term business objectives
- Lead cross-organizational initiatives that have a lasting impact on Atlassianās growth and innovation
ā Required Qualifications
- 15+ years in Data Engineering, Software Engineering, or related roles, with substantial exposure to big data ecosystems
- Demonstrated experience building and operating data platforms or large-scale data services in production
- Proven track record of building services from the ground up (requirements ā design ā implementation ā deployment ā ongoing ownership)
- Hands-on experience with AWS, GCP (e.g., compute, storage, data, and streaming services) and cloud-native architectures
- Practical experience with big data technologies, such as Databricks, Apache Spark, AWS EMR, Apache Flink, or StarRocks
- Strong programming skills in one or more of: Kotlin, Scala, Java, Python
- Experience leading cross-team technical initiatives and influencing senior stakeholders
- Experience mentoring Staff/Principal engineers and lifting the technical bar for a team or org
- Bachelorās or Masterās degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience
ā Preferred Qualifications
- Experience with StarRocks or similar MPP/OLAP analytical databases in production
- Experience with streaming and batch architectures (e.g., event streams, CDC, real-time analytics) and when to use each
- Familiarity with data lakes and table formats (e.g., Iceberg, Delta Lake) and columnar formats such as Parquet
- Exposure to data governance, security, privacy, and compliance (e.g., FedRAMP-like environments) for large-scale data platforms
- Experience optimizing cost, performance, and reliability for petabyte-scale data systems
- Familiarity with observability tooling (metrics, tracing, logging) for data platforms
- Experience contributing to technical strategy and multi-year roadmaps for data platforms
š ļø Required Skills
- AWS
- GCP
- Kubernetes
- Databricks
- Apache Spark
- AWS EMR
- Apache Flink
- StarRocks
- Kotlin
- Scala
- Java
- Python
- Big data ecosystems
- Cloud-native architectures
- Leadership
- Mentoring
- Cross-team collaboration
- Technical strategy
- Observability
- Data governance
- Security
- Privacy
- Compliance
- Cost optimization
- Performance optimization
- Reliability
- Data lakes
- Table formats
- Columnar formats
- Streaming architectures
- Batch architectures
- Event streams
- CDC
- Real-time analytics
š Benefits & Perks
- Health and wellbeing resources
- Paid volunteer days
- Wide range of perks and benefits designed to support you, your family and to help you engage with your local community
Locations
- Multiple Locations, Global
Salary
198,900 - 312,550 USD / yearly
Estimated Salary Rangemedium confidence
250,000 - 350,000 USD / yearly
Source: ai estimated
* This is an estimated range based on market data and may vary based on experience and qualifications.
Skills Required
- AWSintermediate
- GCPintermediate
- Kubernetesintermediate
- Databricksintermediate
- Apache Sparkintermediate
- AWS EMRintermediate
- Apache Flinkintermediate
- StarRocksintermediate
- Kotlinintermediate
- Scalaintermediate
- Javaintermediate
- Pythonintermediate
- Big data ecosystemsintermediate
- Cloud-native architecturesintermediate
- Leadershipintermediate
- Mentoringintermediate
- Cross-team collaborationintermediate
- Technical strategyintermediate
- Observabilityintermediate
- Data governanceintermediate
- Securityintermediate
- Privacyintermediate
- Complianceintermediate
- Cost optimizationintermediate
- Performance optimizationintermediate
- Reliabilityintermediate
- Data lakesintermediate
- Table formatsintermediate
- Columnar formatsintermediate
- Streaming architecturesintermediate
- Batch architecturesintermediate
- Event streamsintermediate
- CDCintermediate
- Real-time analyticsintermediate
Required Qualifications
- 15+ years in Data Engineering, Software Engineering, or related roles, with substantial exposure to big data ecosystems (experience)
- Demonstrated experience building and operating data platforms or large-scale data services in production (experience)
- Proven track record of building services from the ground up (requirements ā design ā implementation ā deployment ā ongoing ownership) (experience)
- Hands-on experience with AWS, GCP (e.g., compute, storage, data, and streaming services) and cloud-native architectures (experience)
- Practical experience with big data technologies, such as Databricks, Apache Spark, AWS EMR, Apache Flink, or StarRocks (experience)
- Strong programming skills in one or more of: Kotlin, Scala, Java, Python (experience)
- Experience leading cross-team technical initiatives and influencing senior stakeholders (experience)
- Experience mentoring Staff/Principal engineers and lifting the technical bar for a team or org (experience)
- Bachelorās or Masterās degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience (experience)
Preferred Qualifications
- Experience with StarRocks or similar MPP/OLAP analytical databases in production (experience)
- Experience with streaming and batch architectures (e.g., event streams, CDC, real-time analytics) and when to use each (experience)
- Familiarity with data lakes and table formats (e.g., Iceberg, Delta Lake) and columnar formats such as Parquet (experience)
- Exposure to data governance, security, privacy, and compliance (e.g., FedRAMP-like environments) for large-scale data platforms (experience)
- Experience optimizing cost, performance, and reliability for petabyte-scale data systems (experience)
- Familiarity with observability tooling (metrics, tracing, logging) for data platforms (experience)
- Experience contributing to technical strategy and multi-year roadmaps for data platforms (experience)
Responsibilities
- Design, develop and own delivery of high quality big data and analytical platform solutions
- Improve and operate large-scale distributed data systems in the cloud (primarily AWS, with increasing integration with GCP and Kubernetes-based microservices)
- Drive the evolution of high-performance analytical databases and its integrations with products, cloud infrastructures (AWS and GCP) and isolated cloud environments
- Help define and uplift engineering and operational standards for petabyte scale data platforms
- Partner across multiple product and platform teams to deliver company-wide initiatives
- Act as a technical mentor and multiplier, raising the bar on design quality, code quality, and operational excellence
- Design and implement self-healing, resilient data platforms with strong observability, fault tolerance, and recovery characteristics
- Own the long-term architecture and technical direction of Atlassianās product data platform
- Be accountable for the reliability, cost efficiency, and strategic direction of Atlassianās product analytical data platform
- Partner with executives and influence senior leaders to align engineering efforts with Atlassianās long-term business objectives
- Lead cross-organizational initiatives that have a lasting impact on Atlassianās growth and innovation
Benefits
- general: Health and wellbeing resources
- general: Paid volunteer days
- general: Wide range of perks and benefits designed to support you, your family and to help you engage with your local community
Tags & Categories
Senior Principal Data Platform Software Engineer
Atlassian
Senior Principal Data Platform Software Engineer
Job Description
Senior Principal Data Platform Software Engineer
š Job Overview
The Senior Principal Data Platform Software Engineer at Atlassian will lead the design and operation of data platform capabilities that support product analytics and ML experiences. This role involves driving the evolution of high-performance analytical databases and ensuring the reliability and strategic direction of Atlassian's product data platform. The position offers the opportunity to influence data platform strategy and shape how product data is managed at scale.
š Location: Multiple Locations, Global
š¢ Category: Engineering
š Posted: 2025-12-11 06:36 PM
šÆ Key Responsibilities
- Design, develop and own delivery of high quality big data and analytical platform solutions
- Improve and operate large-scale distributed data systems in the cloud (primarily AWS, with increasing integration with GCP and Kubernetes-based microservices)
- Drive the evolution of high-performance analytical databases and its integrations with products, cloud infrastructures (AWS and GCP) and isolated cloud environments
- Help define and uplift engineering and operational standards for petabyte scale data platforms
- Partner across multiple product and platform teams to deliver company-wide initiatives
- Act as a technical mentor and multiplier, raising the bar on design quality, code quality, and operational excellence
- Design and implement self-healing, resilient data platforms with strong observability, fault tolerance, and recovery characteristics
- Own the long-term architecture and technical direction of Atlassianās product data platform
- Be accountable for the reliability, cost efficiency, and strategic direction of Atlassianās product analytical data platform
- Partner with executives and influence senior leaders to align engineering efforts with Atlassianās long-term business objectives
- Lead cross-organizational initiatives that have a lasting impact on Atlassianās growth and innovation
ā Required Qualifications
- 15+ years in Data Engineering, Software Engineering, or related roles, with substantial exposure to big data ecosystems
- Demonstrated experience building and operating data platforms or large-scale data services in production
- Proven track record of building services from the ground up (requirements ā design ā implementation ā deployment ā ongoing ownership)
- Hands-on experience with AWS, GCP (e.g., compute, storage, data, and streaming services) and cloud-native architectures
- Practical experience with big data technologies, such as Databricks, Apache Spark, AWS EMR, Apache Flink, or StarRocks
- Strong programming skills in one or more of: Kotlin, Scala, Java, Python
- Experience leading cross-team technical initiatives and influencing senior stakeholders
- Experience mentoring Staff/Principal engineers and lifting the technical bar for a team or org
- Bachelorās or Masterās degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience
ā Preferred Qualifications
- Experience with StarRocks or similar MPP/OLAP analytical databases in production
- Experience with streaming and batch architectures (e.g., event streams, CDC, real-time analytics) and when to use each
- Familiarity with data lakes and table formats (e.g., Iceberg, Delta Lake) and columnar formats such as Parquet
- Exposure to data governance, security, privacy, and compliance (e.g., FedRAMP-like environments) for large-scale data platforms
- Experience optimizing cost, performance, and reliability for petabyte-scale data systems
- Familiarity with observability tooling (metrics, tracing, logging) for data platforms
- Experience contributing to technical strategy and multi-year roadmaps for data platforms
š ļø Required Skills
- AWS
- GCP
- Kubernetes
- Databricks
- Apache Spark
- AWS EMR
- Apache Flink
- StarRocks
- Kotlin
- Scala
- Java
- Python
- Big data ecosystems
- Cloud-native architectures
- Leadership
- Mentoring
- Cross-team collaboration
- Technical strategy
- Observability
- Data governance
- Security
- Privacy
- Compliance
- Cost optimization
- Performance optimization
- Reliability
- Data lakes
- Table formats
- Columnar formats
- Streaming architectures
- Batch architectures
- Event streams
- CDC
- Real-time analytics
š Benefits & Perks
- Health and wellbeing resources
- Paid volunteer days
- Wide range of perks and benefits designed to support you, your family and to help you engage with your local community
Locations
- Multiple Locations, Global
Salary
198,900 - 312,550 USD / yearly
Estimated Salary Rangemedium confidence
250,000 - 350,000 USD / yearly
Source: ai estimated
* This is an estimated range based on market data and may vary based on experience and qualifications.
Skills Required
- AWSintermediate
- GCPintermediate
- Kubernetesintermediate
- Databricksintermediate
- Apache Sparkintermediate
- AWS EMRintermediate
- Apache Flinkintermediate
- StarRocksintermediate
- Kotlinintermediate
- Scalaintermediate
- Javaintermediate
- Pythonintermediate
- Big data ecosystemsintermediate
- Cloud-native architecturesintermediate
- Leadershipintermediate
- Mentoringintermediate
- Cross-team collaborationintermediate
- Technical strategyintermediate
- Observabilityintermediate
- Data governanceintermediate
- Securityintermediate
- Privacyintermediate
- Complianceintermediate
- Cost optimizationintermediate
- Performance optimizationintermediate
- Reliabilityintermediate
- Data lakesintermediate
- Table formatsintermediate
- Columnar formatsintermediate
- Streaming architecturesintermediate
- Batch architecturesintermediate
- Event streamsintermediate
- CDCintermediate
- Real-time analyticsintermediate
Required Qualifications
- 15+ years in Data Engineering, Software Engineering, or related roles, with substantial exposure to big data ecosystems (experience)
- Demonstrated experience building and operating data platforms or large-scale data services in production (experience)
- Proven track record of building services from the ground up (requirements ā design ā implementation ā deployment ā ongoing ownership) (experience)
- Hands-on experience with AWS, GCP (e.g., compute, storage, data, and streaming services) and cloud-native architectures (experience)
- Practical experience with big data technologies, such as Databricks, Apache Spark, AWS EMR, Apache Flink, or StarRocks (experience)
- Strong programming skills in one or more of: Kotlin, Scala, Java, Python (experience)
- Experience leading cross-team technical initiatives and influencing senior stakeholders (experience)
- Experience mentoring Staff/Principal engineers and lifting the technical bar for a team or org (experience)
- Bachelorās or Masterās degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience (experience)
Preferred Qualifications
- Experience with StarRocks or similar MPP/OLAP analytical databases in production (experience)
- Experience with streaming and batch architectures (e.g., event streams, CDC, real-time analytics) and when to use each (experience)
- Familiarity with data lakes and table formats (e.g., Iceberg, Delta Lake) and columnar formats such as Parquet (experience)
- Exposure to data governance, security, privacy, and compliance (e.g., FedRAMP-like environments) for large-scale data platforms (experience)
- Experience optimizing cost, performance, and reliability for petabyte-scale data systems (experience)
- Familiarity with observability tooling (metrics, tracing, logging) for data platforms (experience)
- Experience contributing to technical strategy and multi-year roadmaps for data platforms (experience)
Responsibilities
- Design, develop and own delivery of high quality big data and analytical platform solutions
- Improve and operate large-scale distributed data systems in the cloud (primarily AWS, with increasing integration with GCP and Kubernetes-based microservices)
- Drive the evolution of high-performance analytical databases and its integrations with products, cloud infrastructures (AWS and GCP) and isolated cloud environments
- Help define and uplift engineering and operational standards for petabyte scale data platforms
- Partner across multiple product and platform teams to deliver company-wide initiatives
- Act as a technical mentor and multiplier, raising the bar on design quality, code quality, and operational excellence
- Design and implement self-healing, resilient data platforms with strong observability, fault tolerance, and recovery characteristics
- Own the long-term architecture and technical direction of Atlassianās product data platform
- Be accountable for the reliability, cost efficiency, and strategic direction of Atlassianās product analytical data platform
- Partner with executives and influence senior leaders to align engineering efforts with Atlassianās long-term business objectives
- Lead cross-organizational initiatives that have a lasting impact on Atlassianās growth and innovation
Benefits
- general: Health and wellbeing resources
- general: Paid volunteer days
- general: Wide range of perks and benefits designed to support you, your family and to help you engage with your local community
Tags & Categories