Job Description & How to Apply Below
About the Role
We are seeking a Staff Engineer with a minimum of 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.
This is a full‑time, on‑site position open to candidates with valid work authorization.
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. As a Staff Engineer, 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.
Your technical decisions will shape mission‑critical systems, and your contributions will be visible across the global data ecosystem.
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 Metal, VM, Kubernetes, and multi‑cloud architectures.
Mandatory
Skills & Qualifications
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, Git Hub, 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.
Desired Skills (Bonus)
History of significant contributions or committer status in Apache projects (e.g., Spark, Kafka, Hive, Iceberg, Flink).
Experience with modern table formats (Apache Iceberg, Delta Lake, Hudi) and data lake architectures.
Experience developing or optimizing query engines, query…
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