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Added 3 mins ago
WI
Principal Water Resources Engineer
WSP in Canada
Vancouver, BC
- Full-time
Provide senior technical guidance on water resources assessments within multidisciplinary project teams
Added 3 mins ago
WI
Senior Asset Management Consultant
WSP in Canada
Canada
- Full-time
Ability to communicate effectively with stakeholders at multiple organizational levels, from technical and operational teams to senior leadership.
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WI
Principal Water Resources Engineer
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- Full-time
Provide senior technical guidance on water resources assessments within multidisciplinary project teams
Added 3 mins ago
UO
Incubation Program Lead
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Winnipeg, MB
- $56,966 to $80,280.2 CAD / year
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Added 3 mins ago
WI
Principal Water Resources Engineer
WSP in Canada
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EC
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Added 19 mins ago
UO
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Acceldata

Principal Engineer - Open Source Data Platform (ODP)

Kitchener, ON, Canada

Full-time

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Job details

Job type: Full-time
Apply by: Dec 8, 2026
Experience: 12+ years of hands-on software development experience with at least 8 years focused on distributed systems, big data platforms, or data infrastructure.
Posting language: English
Posted: Oct 15, 2026

Original job description

About Us
Acceldata is the market leader in Enterprise Data Observability. Founded in 2018 and backed by top investors including Insight Partners, March Capital, Lightspeed, Sorenson Ventures, Industry Ventures, and Emergent Ventures, we are a Series-C funded company headquartered in Silicon Valley.

Our Enterprise Data Observability Platform - the first of its kind - helps enterprises build and operate world-class data products by ensuring data is reliable, trusted, and ready to power today’s most critical technologies, including AI, LLMs, Analytics, and DataOps.

Delivered as a SaaS solution, Acceldata is trusted by leading global organizations such as HPE, HSBC, Visa, Freddie Mac, Manulife, Workday, Oracle, PubMatic, PhonePe (Walmart), Hershey’s, Dun & Bradstreet, and many more.

About The Role
We are seeking a Principal Engineer with at least 14 years of experience to serve as a technical visionary and thought leader for Acceldata's Open Data Platform (ODP). In this role, you will define the long-term technical strategy, lead the most complex architectural initiatives, and represent Acceldata in the global open-source and distributed systems community. You will work directly with engineering leadership and executives to shape product direction while driving innovation across the organization.

WHY JOIN US?
As a Principal Engineer at Acceldata, you will be at the forefront of shaping the future of enterprise data platforms, defining the technical vision for systems that power mission-critical workloads across the world's largest organizations. Your decisions will directly influence not only our platform but also the broader data ecosystem through open-source contributions and industry leadership.

You'll work alongside Apache members, committers, and industry veterans who are passionate about solving the hardest problems in distributed computing. This is a rare opportunity to combine deep technical impact with strategic influence, building technology that matters while shaping the direction of a growing data observability company.

Responsibilities

Define and drive the long-term technical strategy and architecture for the Open Data Platform, aligning with business objectives and industry trends.
Own the design of the most complex, high-impact systems and establish architectural principles and patterns that scale across the organization.
Identify emerging technologies and industry trends; lead research and development initiatives that position Acceldata at the cutting edge of data platform innovation.
Serve as a recognized leader in the open-source community; drive Apache project contributions, represent Acceldata at conferences, and influence project roadmaps.
Collaborate with CTO, VP of Engineering, and Product leadership to translate business strategy into technical execution; provide technical due diligence for strategic initiatives.
Influence engineering practices, tools, and culture across multiple teams; establish best practices that elevate the entire engineering organization.
Mentor Staff Engineers and Senior Engineers; develop technical leadership capabilities across the organization.
Lead resolution of the most challenging technical problems spanning architecture, performance, scalability, and reliability.
Engage with strategic customers and partners on complex technical discussions; translate customer needs into platform capabilities.
Drive alignment across engineering, product, and operations on technical decisions with broad organizational impact.
Work across diverse environments: Bare Metals, VM, Kubernetes, multi-cloud, and hybrid architectures at enterprise scale.

Requirements

12+ years of hands-on software development experience with at least 8 years focused on distributed systems, big data platforms, or data infrastructure.
Proven track record of leading large-scale technical initiatives from conception to production across multiple teams.
Expert-level proficiency in Java or Scala; strong skills in Python and systems languages.
Deep expertise in distributed computing, including consensus protocols, distributed transactions, data replication, partitioning strategies, and optimization with modern table formats.
Extensive experience in architecting and scaling systems using Hadoop, Spark, Hive, Trino, Kafka, Flink, and related technologies at production scale (100s to 1000s of nodes).
Demonstrated ability to design and evolve complex systems that handle petabyte-scale data with high availability and performance requirements.
Expert knowledge of cloud-native architectures, Kubernetes orchestration, and multi-cloud deployment patterns.
Track record of diagnosing and resolving complex distributed system issues, including performance optimization, resource management, and failure mode analysis.
Significant contributions to major open-source projects; experience working with distributed global teams and open-source governance models.
Exceptional written and verbal communication skills; proven ability to influence technical direction across organizations and with external stakeholders.
Ability to balance long-term technical vision with near-term delivery requirements; experience making build vs. buy decisions.

DESIRED BACKGROUND

PMC member or committer status in Apache projects (e.g., Spark, Kafka, Hive, Hadoop, Iceberg, Flink, Trino).
Speaker at major conferences (ApacheCon, Spark Summit, Kafka Summit, QCon, etc.); published papers or widely-read technical content.
Experience building or contributing to query engines, optimizers, or execution frameworks.
Deep experience with modern lakehouse architectures, table formats (Iceberg, Delta, Hudi), and data mesh patterns.
Experience with ML infrastructure, feature stores, or MLOps platforms.
Experience scaling engineering organizations in high-growth environments.
Master's or PhD in Computer Science, with a focus on distributed systems, databases, or related fields.

At Acceldata, we are committed to providing equal employment opportunities regardless of job history, disability, gender identity, religion, race, color, caste, marital/parental status, veteran status, or any other special status. We stand against the discrimination of employees and individuals and are proud to be an equitable workplace that welcomes individuals from all walks of life if they fit the designated roles and responsibilities.

is all about working with some of the best minds in the industry and experiencing a culture that values an ‘out-of-the-box’ mindset. If you want to push boundaries, learn continuously, and grow to be the best version of yourself, Acceldata is the place to be!

We also believe in providing our employees with the right tools and resources to help them excel at their jobs. We offer:

PTO Plan with unlimited negative balance
RRSP Plan
Up to 100% employer-paid benefit options for health, dental, and vision coverage
Supplemental Benefits
Apple Air Mac Equipment
Office gym access (includes workout equipment, basketball court, and showers)
Becoming part of the team that coined the term “Data Observability”!

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

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More about this job

Responsibilities

Define the long-term technical strategy and architecture for the Open Data Platform, lead complex system design and problem resolution, and guide innovation across engineering teams. Represent Acceldata in the open-source community, collaborate with executives and customers on technical direction, and mentor senior technical staff.

Requirements

Requires extensive software development experience, including deep expertise in distributed systems, data infrastructure, and production-scale platforms, with expert proficiency in Java or Scala and strong Python skills. Candidates should have led large technical initiatives, contributed significantly to open-source projects, and be experienced with cloud-native architectures, Kubernetes, and petabyte-scale systems; a master's or PhD is listed as desired.

Skills

Distributed Systems
Java
Scala
Python
Big Data Platforms
Apache Spark
Hadoop
Hive
Trino
Kafka
Flink
Kubernetes
Cloud-Native Architecture
Lakehouse Architecture
Open-Source Contributions
Technical Leadership

Benefits

Unlimited Negative-Balance PTO
RRSP Plan
Employer-Paid Health, Dental, and Vision Benefits
Supplemental Benefits
Apple Mac Equipment
Office Gym Access

Visa sponsorship

Not detected in the job text

Keywords

Open Data Platform
Data Observability
Distributed Computing
Distributed Transactions
Consensus Protocols
Data Replication
Data Partitioning
Java
Scala
Python
Hadoop
Apache Spark
Hive
Trino
Kafka
Flink
Kubernetes
Multi-Cloud
Hybrid Architecture
Petabyte-Scale Data
Apache Iceberg
Delta Lake
Apache Hudi
Lakehouse Architecture
Data Mesh
Query Engines
Execution Frameworks
Open-Source Governance
Machine Learning Infrastructure
Feature Stores

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