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Senior Data Engineer, Data Modeling & Streaming

Role overview

Qualifications

  • 5+ years of professional experience in data engineering or distributed systems
  • Strong programming skills using Python
  • Strong programming skills using Java
  • Strong SQL skills

Responsibilities

  • Design logical and physical data models for analytics-ready data platforms
  • Develop ingestion, transformation, and orchestration pipelines
  • Implement data-quality controls and validation logic
  • Troubleshoot production defects and perform root-cause analysis

Key facts

  • Remote from: Canada
  • Full time
  • Senior (5-10 years)
  • Data Engineering Manager
  • 134 - 150K yearly
  • English

Hard skills

Other skills

  • Collaboration
  • Problem Solving

About the company

NEARSOURCE TECHNOLOGIES logo

NEARSOURCE TECHNOLOGIES

IT Services & IT Consulting

NearSource Technologies is one of the leading technology partners for Nearshore Software Development. If you are looking to start on a new Software project and extend your Engineering Team NearSource Technologies serves you with the Managed Services model as well as Resource Augmentation Model that better suits your project requirement. We offer you a flexible and simplified process to build your team with one of the best Engineers in the industry at cost-effective rates. Whether you are looking for a single developer or a fully equipped team, we provide you with the best of technologists who deliver seamless products for your company.

Company details

IndustryIT Services & IT Consulting
Company size501 - 1000

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Job description

Job Title: Senior Data Engineer, Data Modeling & Streaming
Job Location: 100% Remote, Canada
Job Type: T4 Contract
Experience: 8+ Years
Rate: CAD 70 - 78 per hour

Role Summary: NearSource is looking for a Senior Data Engineer to design, develop, test, deploy, and operationalize analytics-ready data models and data pipelines. The role will support a global engineering organization working from a jointly prioritized backlog.

The engineer will contribute across data modeling, batch and streaming pipelines, data quality, testing, production deployment, and operational support.

Key Responsibilities

  • Design logical and physical data models for analytics-ready data platforms.
  • Develop Tier-2 data models using dimensional modeling and star-schema principles where appropriate.
  • Define facts, dimensions, relationships, measures, and data transformations.
  • Develop ingestion, transformation, and orchestration pipelines.
  • Implement batch and streaming data-processing workflows.
  • Support data replication and historical data backfills.
  • Implement data-quality controls and validation logic.
  • Execute unit, integration, regression, and data-quality testing.
  • Reconcile source and target datasets to validate data accuracy and completeness.
  • Prepare production-ready code, configurations, and data models.
  • Participate in code reviews and approved release processes.
  • Support production deployments and post-deployment validation.
  • Troubleshoot production defects and perform root-cause analysis.
  • Create technical documentation, release notes, and operational materials.
  • Participate in daily stand-ups, design reviews, demonstrations, and knowledge-transfer activities.
  • Support collaboration with distributed global engineering teams across AMER-aligned engineering activities, stakeholder discussions, technical reviews, and delivery.

Must-Have Skills

  • 5+ years of professional experience in data engineering or distributed systems.
  • Strong production experience with batch and streaming data architectures.
  • Experience building and maintaining production data pipelines.
  • Experience with dimensional data modeling and star-schema design.
  • Strong programming skills using Python.
  • Strong programming skills using Java.
  • Strong SQL skills.
  • Experience with data quality and automated testing.
  • Experience with production troubleshooting and root-cause analysis.
  • Experience with source control, CI/CD, code reviews, and agile engineering practices.
  • Experience working effectively within a distributed global engineering team.
  • Hands-on experience with Apache Iceberg.
  • Hands-on experience with Apache Airflow.
  • Hands-on experience with Apache Spark.
  • Hands-on experience with Apache Kafka.
  • Hands-on experience with Apache Flink.
  • Hands-on experience with Snowflake.
  • Experience with Amazon Web Services.

Expected Deliverables

  • Completed source code, configurations, and data models.
  • Technical and operational documentation.
  • Approved pull requests.
  • Testing and validation evidence.
  • Engineering demonstrations or technical walkthroughs.
  • Release notes and change summaries.
  • Production deployment artifacts.
  • Post-release validation.
  • Knowledge transfer and documented handoff of remaining work.

Apply now, or share your resume with salary expectations at careers@nearsource.ca.
Thank you for considering a career with us! Once you submit your application, our Talent Acquisition team will review your resume thoroughly. If there's a strong match, we'll reach out to discuss your experience, role details, benefits, compensation, and next steps. While we strive for transparency, we may not be able to respond to every applicant due to high volume, but we genuinely appreciate your time and interest.

About NearSource: NearSource Technologies is a trusted partner for future-ready software consulting, enabling Fortune 500 enterprises to accelerate digital transformation. Our global engineering teams build and deploy impactful technology for some of the world's most admired brands, working directly on long-term client initiatives.

Equal Opportunity: NearSource is an equal opportunity employer committed to fostering an inclusive and respectful environment. We celebrate diversity and do not discriminate based on race, gender, religion, sexual orientation, age, disability, or background. Innovation thrives when everyone feels empowered to contribute.

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Marcus Rivera

Chief Revenue Officer

m.rivera@company.com
linkedin.com/in/marcusrivera
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