---
title: 'Staff Software Engineer - Open Source Data Platform (ODP) at Acceldata'
canonical: 'https://feeny.ai/job/staff-software-engineer-open-source-data-platform-odp-acceldata-kitchener-1mw600fhgy17'
type: 'job'
last_seen: '2026-09-10'
---

# Staff Software Engineer - Open Source Data Platform (ODP) at Acceldata

- **Company:** Acceldata
- **Location:** Kitchener, Canada
- **Compensation:** $180k–$210k
- **Employment:** full-time
- **Work type:** onsite
- **Posted:** 2026-03-16
- **Last confirmed live:** 2026-09-10
- **Apply:** https://jobs.lever.co/acceldata/ef679998-fbd9-45c8-a3e2-a675a93ed37f

## Job description

## ABOUT THE ROLE

We are seeking a Staff Engineer with at least 9 years of experience in distributed systems or data platform development. In this role, you will be a technical leader responsible for architecting and driving the technical direction of critical components within the Acceldata Open Data Platform (ODP). You will work on solving the most challenging distributed systems problems, contribute to open-source communities, and mentor senior engineers while shaping the future of large-scale data infrastructure.

You'll lead high-impact initiatives that directly influence how petabyte-scale data is managed, observed, and optimized across hybrid and cloud ecosystems. You'll collaborate with industry experts, Apache committers, and seasoned engineers who share your passion for distributed systems and open-source innovation.

## WHY JOIN US

At Acceldata, you won't just be writing code; you'll be defining the architecture and technical vision for modern data platforms used by some of the world's largest enterprises.

Your technical decisions will shape mission-critical systems, and your contributions will be visible across the global data ecosystem. If you're ready to take ownership of complex technical challenges and drive innovation at scale, Acceldata is where you belong.

## RESPONSIBILITIES

- Own the end-to-end architecture of major platform components, driving design decisions that impact scalability, reliability, and performance.
- Architect and implement next-generation distributed data storage, processing, and query optimization systems.
- Partner with product, engineering leadership, and stakeholders to define technical roadmaps and translate business requirements into scalable solutions.
- Lead contributions to Apache projects and open-source communities, establishing Acceldata's presence and technical reputation.
- Identify and resolve complex performance bottlenecks across distributed systems, optimizing for cost, latency, and throughput.
- Mentor and guide Senior Software Engineers, fostering technical excellence and a culture of continuous learning.
- Establish and enforce coding standards, perform thorough code reviews, and ensure architectural consistency across the platform.
- Evaluate and recommend emerging technologies, tools, and frameworks that align with platform goals.
- Lead root cause analysis for critical production issues and drive systemic improvements to prevent recurrence.
- Work across diverse environments: Bare Metals, VM, Kubernetes, and multi-cloud architectures.

## REQUIREMENTS

- 9+ years of hands-on software development experience with at least 5 years focused on distributed systems or big data platforms.
- Expert-level proficiency in Java or Scala, with strong Python skills. Experience with systems languages is a plus.
- Deep understanding of distributed computing principles, including consensus algorithms, data partitioning, replication, fault tolerance, and consistency models.
- Extensive hands-on experience with multiple components of the big data stack (Hadoop, Spark, Hive, Trino, Kafka, Flink, NiFi or similar).
- Expert-level Linux proficiency, including kernel tuning, performance analysis, and debugging at the system level.
- Strong experience with Kubernetes, Docker, and cloud platforms (AWS, GCP, or Azure).
- Deep expertise with Maven, Gradle, or SBT; experienced in CI/CD pipelines, GitHub, and artifact management (Nexus).
- Proven ability to diagnose and resolve complex issues, including memory leaks, deadlocks, GC tuning, and distributed system failures.
- Strong understanding of architectural patterns for scalable, fault-tolerant distributed systems.
- Excellent written and verbal communication skills; ability to articulate complex technical concepts to diverse audiences, including senior leadership.
- Demonstrated ability to work effectively with cross-functional teams, external contributors, and the open-source community.

## PREFERRED SKILLS

- History of significant contributions or committer status in Apache projects (e.g., Spark, Kafka, Hive, Iceberg, Flink, etc.).
- Experience with modern table formats (Apache Iceberg, Delta Lake, Hudi) and data lake architectures.
- Experience developing or optimizing query engines, query planners, or execution frameworks.
- Familiarity with data governance, security, lineage, and compliance frameworks.
- Experience leading large-scale data platform migrations or Hadoop distribution upgrades.
- Published technical blogs, papers, or conference presentations on distributed systems topics.
- Experience leading or maintaining open-source projects.

## About Acceldata

## Company Overview
- **One-liner**: Acceldata provides an autonomous agentic data management platform that enables enterprises to observe, govern, and optimize complex data and AI workloads across hybrid cloud environments.
- **Entity Type**: Private (Series C)
- **Headquarters**: Campbell, California, USA
- **Founded**: 2018
- **Founders**: Rohit Choudhary (CEO), Ashwin Rajeeva (CTO), Raghu Kandikonda (Co-Founder & VP Engineering)

## Core Business
- **Primary industry**: Data Observability, Agentic Data Management, AI Infrastructure
- **Target customers**: Large enterprises (B2B, Enterprise) – customers include Dun & Bradstreet, AT&T, Oracle, DBS
- **Mission statement**: Deliver the promise of data quality and reliability at exabyte scale, blending the best of on-premises and cloud worlds, and providing real-time AI monitoring with structured, unstructured, and streaming data inputs.

## Products & Services
- **Data & AI Observability**: End-to-end visibility into AI agents, Hadoop, data quality, pipelines, and platforms.
- **Agentic Data Management**: Autonomous detection, diagnosis, and resolution across the data estate.
- **Data Warehousing**: Modern data warehousing capabilities built on the xLake platform.
- **Data Platform Modernization**: Open-source foundation for Hadoop modernization across cloud, on-prem, and hybrid environments.
- **xLake Platform**: The unified, customer-controlled control plane that runs every Acceldata product. Federated compute planes execute workloads where data resides, with built-in governance, observability, and lineage.

## Market Standing
- **Valuation**: Not publicly disclosed
- **Key Metric**: Total Funding – Series C round (amount undisclosed); over 1 trillion data and agent interactions daily; 200+ teams worldwide rely on Acceldata.
- **Notable Investors/Partners**: Insight Partners (lead investor); key customers include Dun & Bradstreet, AT&T, Oracle, DBS.
- **Growth Signals**: Headcount growth to 201–1000 employees; expansion into Canada (Kitchener) and UK (London); new product launches (xLake, Agentic Data Management); recognition as pioneer and leader in data observability category.

## Competitive Advantages
- First to coin the term “Data Observability” and pioneer the category.
- Unified xLake platform with a single control plane that works across hybrid cloud, on-prem, and edge.
- Patented technology in data processing and related fields; contributions to Apache Ambari and Apache Zeppelin.
- Deep expertise in complex data systems from founders’ experience at Hortonworks, Zalando, and Adobe.
- Agentic approach – autonomous detection and resolution reduces manual intervention.

## Strategic Focus
- Accelerating enterprise adoption of autonomous data management and AI agents.
- Expanding hybrid cloud capabilities so workloads run where data lives.
- Enhancing the agentic brain for orchestration, governance, and observability of AI agents and data pipelines.
- Growing the platform from a single product to a suite of products (Observability, Data Management, Warehousing, Modernization) that can be used individually or together.

## Why Work Here
- **Culture highlights**: Acceldata describes itself as a dynamic, innovative environment where creativity thrives, ideas flourish, and collaboration fuels breakthroughs. Values curiosity, diversity, and a shared commitment to excellence.
- **Remote/hybrid/office policy**: Multiple office locations (Campbell HQ, Bangalore, Kitchener, London). Job postings indicate on-site, hybrid, and full-time remote options depending on role.
- **Notable perks/engineering culture**: Deep technical roots in open-source (Apache projects) and big data systems. Opportunity to work on cutting-edge data observability and AI agent infrastructure at scale. Leadership team includes experienced executives from Hortonworks, Adobe, and other tech leaders. Series C funding provides stability and growth trajectory.

## Sources
1. [acceldata.io/about-us](https://www.acceldata.io/about-us)
2. [acceldata.io/careers](https://www.acceldata.io/careers)
3. [acceldata.io](https://www.acceldata.io/)
4. [jobs.lever.co/acceldata](https://jobs.lever.co/acceldata)
5. [jobs.insightpartners.com/companies/acceldata](https://jobs.insightpartners.com/companies/acceldata)

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