Principal Engineer, Streaming Systems Job at Hightouch

Principal Data Engineer

PointClickCare is searching for a Principal Data Engineer who will contribute to...

Location

United States

Salary:

183200.00 - 203500.00 USD / Year

PointClickCare

Expiration Date

Until further notice

Requirements

Principal Data Engineer with at least 10 years of professional experience in software or data engineering, including a minimum of 4 years focused on streaming and real-time data systems
Proven experience driving technical direction and mentoring engineers while delivering complex, high-scale solutions as a hands-on contributor
Deep expertise in streaming and real-time data technologies, including frameworks such as Apache Kafka, Flink, and Spark Streaming
Strong understanding of event-driven architectures and distributed systems, with hands-on experience implementing resilient, low-latency pipelines
Practical experience with cloud platforms (AWS, Azure, or GCP) and containerized deployments for data workloads
Fluency in data quality practices and CI/CD integration, including schema management, automated testing, and validation frameworks (e.g., dbt, Great Expectations)
Operational excellence in observability, with experience implementing metrics, logging, tracing, and alerting for data pipelines using modern tools
Solid foundation in data governance and performance optimization, ensuring reliability and scalability across batch and streaming environments
Experience with Lakehouse architectures and related technologies, including Databricks, Azure ADLS Gen2, and Apache Hudi
Strong collaboration and communication skills, with the ability to influence stakeholders and evangelize modern data practices within your team and across the organization

Job Responsibility

Lead and guide the design and implementation of scalable streaming data pipelines
Engineer and optimize real-time data solutions using frameworks like Apache Kafka, Flink, Spark Streaming
Collaborate cross-functionally with product, analytics, and AI teams to ensure data is a strategic asset
Advance ongoing modernization efforts, deepening adoption of event-driven architectures and cloud-native technologies
Drive adoption of best practices in data governance, observability, and performance tuning for streaming workloads
Embed data quality in processing pipelines by defining schema contracts, implementing transformation tests and data assertions, enforcing backward-compatible schema evolution, and automating checks for freshness, completeness, and accuracy across batch and streaming paths before production deployment
Establish robust observability for data pipelines by implementing metrics, logging, and distributed tracing for streaming jobs, defining SLAs and SLOs for latency and throughput, and integrating alerting and dashboards to enable proactive monitoring and rapid incident response
Foster a culture of quality through peer reviews, providing constructive feedback and seeking input on your own work

What we offer

Benefits starting from Day 1!
Retirement Plan Matching
Flexible Paid Time Off
Wellness Support Programs and Resources
Parental & Caregiver Leaves
Fertility & Adoption Support
Continuous Development Support Program
Employee Assistance Program
Allyship and Inclusion Communities
Employee Recognition … and more!

Fulltime

Principal Data Engineer

Atlassian is looking for a Principal Data Engineer to join our Data Engineering ...

Location

United States , San Francisco

Salary:

168700.00 - 271100.00 USD / Year

Atlassian

Expiration Date

Until further notice

Requirements

You have 12+ years of experience in a Data Engineer role as an individual contributor
You have at least 2 years of experience as a tech lead for a Data Engineering team
You are an engineer with a track record of driving and delivering large (multi-person or multi-team) and complex efforts
You are a great communicator and maintain many of the essential cross-team and cross-functional relationships necessary for the team's success
Experience with building streaming pipelines with a micro-services architecture for low-latency analytics
Experience working with varied forms of data infrastructure, including relational databases (e.g. SQL), Spark, and column stores (e.g. Redshift)
Experience building scalable data pipelines using Spark using Airflow scheduler/executor framework or similar scheduling tools
Experience working in a technical environment with the latest technologies like AWS data services (Redshift, Athena, EMR) or similar Apache projects (Spark, Flink, Hive, or Kafka)
Understanding of Data Engineering tools/frameworks and standards to improve the productivity and quality of output for Data Engineers across the team
Industry experience working with large-scale, high-performance data processing systems (batch and streaming) with a 'Streaming First' mindset to drive Atlassian's business growth and improve the product experience

Job Responsibility

Own the technical evolution of the data engineering capabilities and be responsible for ensuring solutions are being delivered incrementally, meeting outcomes, and promptly escalating risks and issues
Establish a deep understanding of how things work in data engineering, use this to direct and coordinate the technical aspects of work across data engineering, and systematically improve productivity across the teams
Maintain a high bar for operational data quality and proactively address performance, scale, complexity and security considerations
Drive complex decisions that can impact the work in data engineering. Set the technical direction and balance customer and business needs with long-term maintainability & scale
Understand and define the problem space, and architect solutions. Coordinate a team of engineers towards implementing them, unblocking them along the way if necessary
Lead a team of data engineers through mentoring and coaching, work closely with the engineering manager, and provide consistent feedback to help them manage and grow the team
Work with close counterparts in other departments as part of a multi-functional team, and build this culture in your team

What we offer

health coverage
paid volunteer days
wellness resources

Fulltime

AI Machine Learning Principal Engineer

Our Regulatory Engineering team thrives on the challenge of operating in a compl...

Location

Singapore , Singapore

Salary:

Not provided

Dell

Expiration Date

March 31, 2026

Requirements

Requires 8+ years of related experience in a professional role with a Bachelor’s degree
or 6+ years with a Master’s degree
or 3+ years with a PhD
or equivalent experience
Knowledge on product compliance, Safety, EMC, Wireless, Telecom and Environmental (e.g. Energy, Material, ECO Labels, Accessibility, Repairability, Packaging and etc.) legislation programs will be plus
Track record of being an enthusiastic and effective team player with experience leading and influencing internal and external stakeholders to ensure successful outcomes

Job Responsibility

Apply knowledge of AI machine learning, statistics, optimization, software engineering and data engineering to produce code for testing, operationalizing and governing software-integrated machine learning models
Works with stakeholders including business owners, software engineers, data scientists and data engineers to align and execute end-to-end solutions which start with data collection and management, extend through machine learning methodologies and efficiencies in software engineering, and end with governance of machine learning model performance
Optimizes code for existing data streams, machine learning models and APIs using best practices in software engineering and experimental design
Defines best practices for AI ML engineering, code optimization, model and system validation and model governance and educates prospects and customers on analytics and machine learning offerings
Leads the design and testing of analytical technologies, or the development/testing of new algorithms/functions to enhance capabilities within key market segments of interest
Leads definition of machine learning and data analytics vision, multiple use-case evaluation and selection criteria, as well as project-level scope definition for customers
Proactively identifies gaps and collaborates with engineering teams to find solutions, while solidifying commitments to execute these
Drives partnerships & relationships with third parties to develop vertical/horizontal analytical solutions and product integrations

What we offer

Comprehensive Healthcare Programs
Award Winning Financial Wellness Tools and Resources
Generous Leave of Absence for New Parents and Caregivers
Industry Leading Wellness Platform
Employee Assistance Program

Principal Data Engineer

Atlassian is looking for a Principal Data Engineer to join our Data Engineering ...

Location

United States , San Francisco; Seattle; Austin

Salary:

168700.00 - 271100.00 USD / Year

Atlassian

Expiration Date

Until further notice

Requirements

12+ years of experience in a Data Engineer role as an individual contributor
At least 2 years of experience as a tech lead for a Data Engineering team
Engineer with a track record of driving and delivering large (multi-person or multi-team) and complex efforts
Great communicator and maintain many of the essential cross-team and cross-functional relationships necessary for the team's success
Experience with building streaming pipelines with a micro-services architecture for low-latency analytics
Experience working with varied forms of data infrastructure, including relational databases (e.g. SQL), Spark, and column stores (e.g. Redshift)
Experience building scalable data pipelines using Spark using Airflow scheduler/executor framework or similar scheduling tools
Experience working in a technical environment with the latest technologies like AWS data services (Redshift, Athena, EMR) or similar Apache projects (Spark, Flink, Hive, or Kafka)
Understanding of Data Engineering tools/frameworks and standards to improve the productivity and quality of output for Data Engineers across the team
Industry experience working with large-scale, high-performance data processing systems (batch and streaming) with a "Streaming First" mindset to drive Atlassian's business growth and improve the product experience

Job Responsibility

Own the technical evolution of the data engineering capabilities and be responsible for ensuring solutions are being delivered incrementally, meeting outcomes, and promptly escalating risks and issues
Establish a deep understanding of how things work in data engineering, use this to direct and coordinate the technical aspects of work across data engineering, and systematically improve productivity across the teams
Maintain a high bar for operational data quality and proactively address performance, scale, complexity and security considerations
Drive complex decisions that can impact the work in data engineering
Set the technical direction and balance customer and business needs with long-term maintainability & scale
Understand and define the problem space, and architect solutions
Coordinate a team of engineers towards implementing them, unblocking them along the way if necessary
Lead a team of data engineers through mentoring and coaching, work closely with the engineering manager, and provide consistent feedback to help them manage and grow the team
Work with close counterparts in other departments as part of a multi-functional team, and build this culture in your team

What we offer

Health coverage
Paid volunteer days
Wellness resources

Fulltime

Principal Data Engineer

Atlassian is looking for a Principal Data Engineer to join our Corporate Data En...

Location

United States , San Francisco; Mountain View

Salary:

168700.00 - 271100.00 USD / Year

Atlassian

Expiration Date

Until further notice

Requirements

12+ years of experience in a Data Engineer role as an individual contributor
at least 2 years of experience as a tech lead for a Data Engineering team
track record of driving and delivering large and complex efforts
great communicator and maintain cross-team and cross-functional relationships
experience with building streaming pipelines with a micro-services architecture for low-latency analytics
experience working with varied forms of data infrastructure, including relational databases (e.g. SQL), Spark, and column stores (e.g. Redshift)
experience building scalable data pipelines using Spark using Airflow scheduler/executor framework or similar scheduling tools
experience working in a technical environment with the latest technologies like AWS data services (Redshift, Athena, EMR) or similar Apache projects (Spark, Flink, Hive, or Kafka)
understanding of Data Engineering tools/frameworks and standards to improve the productivity and quality of output for Data Engineers across the team
industry experience working with large-scale, high-performance data processing systems (batch and streaming) with a "Streaming First" mindset

Job Responsibility

help our stakeholder teams ingest data faster into our data lake
find ways to make our data pipelines more efficient
come up ideas to help instigate self-serve data engineering within the company
building micro-services, architecting, designing, and enabling self serve capabilities at scale to help Atlassian grow

What we offer

health coverage
paid volunteer days
wellness resources

Fulltime

Senior Principal Data Engineer

Atlassian is looking for a Senior Principal Data Engineer to join the Go-To Mark...

Location

United States , San Francisco

Salary:

Not provided

Atlassian

Expiration Date

Until further notice

Requirements

18+ years of experience in a Data Engineer role as an individual contributor
at least 7 years of experience as a tech lead for Data Engineering teams, and delivered complex, cross-team initiatives
built durable relationships with executives/senior leaders across Sales, Marketing, Finance, Commerce and related organizations, and understand complexities of data in these organizations
a track record of driving and delivering large complex, multi-team efforts
a great communicator and maintain many of the essential cross-team and cross-functional relationships necessary for the team's success
experience with building streaming pipelines with a micro-services architecture for low-latency analytics
experience working with varied forms of data infrastructure, including relational databases (e.g. SQL), Spark, dbt, and column stores (e.g. Redshift)
experience building scalable data pipelines using Spark using Airflow scheduler/executor framework or similar scheduling tools
experience working in a technical environment with the latest technologies like AWS data services (Redshift, Athena, EMR) or similar Apache projects (Spark, Flink, Hive, or Kafka)
understanding of Data Engineering tools/frameworks and standards to improve the productivity and quality of output for Data Engineers across the team

Job Responsibility

Help stakeholder teams ingest data faster into our data lake
find ways to make data pipelines more efficient
come up with ideas to help instigate self-serve data engineering within the company
building micro-services, architecting, designing, and enabling self-serve capabilities at scale to help Atlassian grow

What we offer

health coverage
paid volunteer days
wellness resources

Fulltime

Principal Data Engineer

We are on the lookout for a Principal Data Engineer to help define and lead the ...

Location

United Kingdom

Salary:

Not provided

Dotdigital

Expiration Date

Until further notice

Requirements

Extensive experience delivering python-based projects in the data engineering space
Extensive experience working with SQL and NoSQL database technologies (e.g. SQL Server, MongoDB & Cassandra)
Proven experience with modern data warehousing and large-scale data processing tools (e.g. Snowflake, DBT, BiqQuery, Clickhouse)
Hands on experience with data orchestration tools like Airflow, Dagster or Prefect
Experience using cloud environments (e.g. Azure, AWS, GCP) to process, store and surface large scale data
Experience using Kafka or similar event-based architectures e.g. (Pub/Sub via AWS SQS, Azure EventHubs, AWS Kinesis)
Strong grasp of data architecture and data modelling principles for both OLAP and OLTP workloads
Capable in the wider software development lifecycle in terms of agile ways of working and continuous integration/deployment of data solutions
Experience as a lead or Principal Engineer on large-scale data initiative or product builds
Demonstrated ability to architect data systems and data structures for high volume, high throughput systems

Job Responsibility

Lead the design and implementation of scalable, secure and resilient data systems across streaming, batch and real-time use cases
Architect data pipelines, model and storage solutions that power analytical and product use cases
using primarily Python and SQL via orchestration tooling that run workloads in the cloud
Leverage AI to automate both data processing and engineering processes
Assure and drive best practices relating to data infrastructure, governance, security and observability
Work with technologists across multiple teams to deliver coherent features and data outcomes
Support the data team to help adopt data engineering principles
Identify, validate and promote new tools and technologies that improve the performance and stability of data services

What we offer

Parental leave
Medical benefits
Paid sick leave
Dotdigital day
Share reward
Wellbeing reward
Wellbeing Days
Loyalty reward

Fulltime