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Salary
≈ $97k – $167k per year (Estimated)
Location
In office (Kitchener)
Seniority
Principal · 14+ years exp
Employment
Full-Time

Confirmed on the employer's own hiring board on Oct 16, 2026. First seen by Alion on Mar 16, 2026. Acceldata scores B on the Alion truth index.

Overview
Company
Impact
Profile match
Acceldata is a data observability and data platform software company headquartered in Campbell, California, that helps enterprises monitor, manage and optimize data and AI workloads across cloud, hybrid and on-premises environments. Founded in 2018, it offers the Acceldata Data Observability Cloud, the Pulse Hadoop observability product, the xLake platform and an Open Data Platform built on Hadoop, Spark, Hive, Kafka and Trino, with engineering centered in Bengaluru. It hires software, frontend and open source engineers, SREs, SDETs, solutions consultants, technical account managers and enterprise sales and marketing staff in Bengaluru, Kitchener, London and Campbell.

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.
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