Staff Data Engineer

Sonatype

Staff Data Engineer building scalable pipelines and lakehouse architecture for Sonatype, a software supply chain security company. Driving trusted analytics, ML, and business intelligence data with Databricks, Spark, and modern cloud technologies.

Posted 8/17/2026full-timeRemote • 🇨🇦 CanadaLeadWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and maintaining scalable data pipelines and ETL/ELT processes, with a strong focus on data modeling, observability, and cloud data platforms. Proven ability to collaborate with cross-functional teams and mentor others in data engineering best practices.

Highest-signal resume keywords

Data Pipeline DesignDatabricks OptimizationPython ProgrammingETL/ELT ProcessesCloud Data Platforms

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data Modeling TechniquesSQL Query OptimizationNoSQL Query OptimizationAI/ML TechnologiesDistributed Data SystemsData ObservabilityStreaming Data ArchitecturesDelta Lake ArchitectureCI/CD Best PracticesData Quality Monitoring

Soft Skills

CollaborationMentoringStakeholder Engagement

Tools & Technologies

DatabricksSparkAirflowAWSKafkaDelta LakeApache IcebergApache HudiDagsterAI-Assisted Development Tools

Industry Keywords

Data EngineeringData Lakehouse ArchitectureSoftware Supply ChainCybersecurityLarge-Scale Software Ecosystem Data

Tech Stack

Tools & technologies

AirflowApacheAWSCloudCyber SecurityETLJavaKafkaNoSQLPythonScalaSparkSQL

About the role

Key responsibilities & impact

Design, build, and maintain scalable data pipelines and ETL/ELT processes
Architect and optimize data models and storage solutions for analytics and operational use
Collaborate with data scientists, analysts, and engineers to deliver trusted, high-quality datasets
Own and evolve parts of the data platform using Databricks and Spark
Implement observability, alerting, and data quality monitoring for critical pipelines
Drive data engineering best practices, including documentation, testing, and CI/CD
Drive long-term architectural vision and mentor the team on engineering best practices
Partner with stakeholders to ensure data solutions support business outcomes
Contribute to the design and evolution of the next-generation data lakehouse architecture

Requirements

What you’ll need

8+ years of experience as a Data Engineer or similar backend engineering role
Bachelor’s degree in Computer Science, Engineering, or related technical field
Databricks optimization, including tuning Spark jobs, optimizing joins, and managing Delta Lake architecture
Experience with AI-assisted development tools and AI/ML technologies
Strong programming skills in Python, Scala, or Java
Hands-on experience with distributed data systems such as Spark or Kafka
Proficiency writing and optimizing complex SQL and NoSQL queries
Experience building and maintaining robust production ETL/ELT pipelines
Understanding of data modeling techniques, including star schema and dimensional modeling
Familiarity with software supply chain, cybersecurity, or large-scale software ecosystem data
Track record improving data platform reliability, scalability, performance, and cost efficiency
Familiarity with workflow orchestration tools such as Airflow or Dagster
Hands-on experience with cloud data platforms, particularly AWS
Familiarity with Delta Lake, Apache Iceberg, or Apache Hudi
Experience implementing data observability, lineage, governance, and automated data quality frameworks
Experience designing real-time or streaming data architectures using data lake technologies

Benefits

Comp & perks

Parental leave
Diversity and inclusion working groups
Flexible working practices
Paid Volunteer Time Off (VTO)