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.
