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Principal Java Data Engineer

Skills

aianalyticsawsazureci cdclouddata engineeringdata governancedata pipelinesdata qualitydatabricksdbtdistributed systemsevent driven architecturegcpjavalakehousemicroservicesobservabilitysparktest automationtrinoJavaAzure

Description

Job Description

Job Description

Role: Principal Java Data Engineer

Location: Canada (Remote)

Long Term contract

Mandatory skill:- Spec-Driven Development (SDD) is Must with AI

Ideal Experience

  • Lead and guide the design and implementation of scalable distributed systems based on Java microservices
  • Engineer and optimize data pipelines using solutions like Apache Hudi, Apache Trino, Azure ADLS
  • Collaborate cross-functionally with product, analytics, and AI teams to ensure data is a strategic asset
  • Principal Software Data Engineer with at least 10 years of professional experience in software or data engineering, including a minimum of 4 years focused on data pipelines (batch and streaming)
  • Proven experience driving technical direction and mentoring engineers while delivering complex, high-scale solutions as a hands-on contributor
  • Strong understanding of event-driven architectures and distributed systems, with hands-on experience implementing resilient, low-latency pipelines
  • Practical experience with cloud platforms (AWS, Azure, or GCP) and containerized deployments for data workloads
  • Fluency in data quality practices and CI/CD integration, including schema management, automated testing, and validation frameworks (e.g., dbt, Great Expectations)
  • Operational excellence in observability, with experience implementing metrics, logging, tracing, and alerting for data pipelines using modern tools
  • Solid foundation in data governance and performance optimization, ensuring reliability and scalability across batch and streaming environments
  • Proven experience with Lakehouse architectures and related technologies, including Apache Hudi, Azure ADLS Gen2, HDFS, and other big data technologies (Trino, Databricks, Spark)
  • Strong collaboration and communication skills, with the ability to influence stakeholders and evangelize modern data practices within your team and organization.

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