3 дня назад
Principal Java Data Engineer
156 000 - 174 000CAD
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Principal Java Data Engineer (Data Platforms): Designing and maintaining large-scale data platforms and batch and real-time pipelines based on Java microservices with an accent on lakehouse architectures, event-driven systems, data quality, and observability. Focus on building resilient distributed pipelines, enforcing schema and validation contracts, implementing metrics and tracing, and mentoring engineers as a hands-on technical leader.
Location: Hybrid in Mississauga, Canada, with residence within commuting distance of the office required
Salary: CAD 156,000–174,000 per year, plus bonus and benefits
Company
is a privately held health technology company providing a healthcare platform and data ecosystem for long-term and post-acute care providers across North America.
What you will do
- Lead the design and implementation of scalable distributed systems using Java microservices.
- Build and optimize batch and real-time data pipelines with Apache Hudi, Apache Trino, Azure ADLS, and related technologies.
- Advance event-driven architecture, cloud-native modernization, and containerized data workloads.
- Implement data quality controls, schema contracts, transformation tests, assertions, and automated freshness, completeness, and accuracy checks.
- Establish observability through metrics, logging, distributed tracing, SLAs, SLOs, alerting, and dashboards for data pipelines.
- Provide technical leadership, mentor engineers, and collaborate with product, analytics, and AI teams.
Requirements
- At least 10 years of professional software or data engineering experience, including at least 4 years focused on batch and streaming data pipelines.
- Hands-on experience leading technical direction, mentoring engineers, and delivering high-scale solutions.
- Strong knowledge of event-driven architectures, distributed systems, resilient low-latency pipelines, and cloud platforms such as AWS, Azure, or GCP.
- Experience with data quality, schema management, automated testing, validation frameworks, CI/CD, and data governance.
- Experience with observability tools and practices, including metrics, logging, tracing, alerting, and performance optimization.
- Experience with lakehouse and big data technologies, including Apache Hudi, Azure ADLS Gen2, HDFS, Trino, Databricks, and Spark.
Culture & Benefits
- Benefits begin on the first day of employment.
- Retirement plan matching and flexible paid time off.
- Wellness support, employee assistance, and parental, caregiver, fertility, and adoption programs.
- Continuous development support and employee recognition programs.
- Inclusive employee communities and a collaborative, quality-focused engineering culture.
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