Data Engineer

Data EngineerData EngineerFull TimeRemoteSeniorTeam 5,001-10,000H1B SponsorCompany SiteLinkedIn

Location

Canada

Posted

1 day ago

Salary

$110K - $140K / year

Seniority

Senior

Bachelor Degree4 yrs expEnglishAzureCloudETLPythonSQL

Job Description

Data Engineer

Teladoc Health

• Design, build, and maintain batch, incremental, and file-based data pipelines to support analytics, reporting, and operational use cases. • Support data migration initiatives, including the movement of data from legacy systems to modern platforms, ensuring continuity, accuracy, and reconciliation. • Work with enterprise data integration tools such as Talend, including maintaining existing Talend jobs and supporting the migration or re-implementation of Talend pipelines into other platforms where required. • Establish and maintain a robust data engineering environment (e.g., dev/test/prod separation, access controls, naming standards, source control, deployment processes, and monitoring) that enables reliable delivery and safe change management. • Support ingestion, storage, and management of unstructured and semi-structured datasets (e.g., documents, PDFs, text extracts, files, metadata) alongside traditional relational data. • Support and optimize data models in Power BI dashboards and AI-enabled analytics. • Prepare and curate analytics- and AI-ready datasets, including clean, well-defined tables and reference data used in automation and AI-enabled solutions. • Collaborate closely with AI & Automation Specialists to ensure data requirements for AI initiatives are well understood, properly sourced, validated, and production-ready. • Translate business and reporting requirements into scalable data models, transformations, and pipeline designs. • Develop and maintain trusted datasets that support dashboards, scorecards, client reporting, and downstream analytics. • Implement data quality checks, validation logic, reconciliation processes, and monitoring to ensure data reliability and consistency. • Troubleshoot and resolve data issues across ingestion, transformation, and consumption layers, identifying root causes and remediation actions. • Develop and maintain clear documentation, including source-to-target mappings, data definitions, data lineage, and known limitations. • Work in partnership with analytics, IT, data governance, and security stakeholders to ensure data solutions comply with privacy, security, and regulatory expectations. • Contribute to the prioritization, planning, and delivery of multiple data engineering, migration, and enablement initiatives in parallel.

Job Requirements

  • Bachelor’s Degree in Computer Science, Information Technology, Data Analytics or related field
  • 4+ year experience working in data engineering, analytics engineering, business intelligence, or data platform roles.
  • 4+ years Experience with data integration and ETL/ELT tools (e.g., Talend, Azure Data Factory, or similar enterprise platforms).
  • Experience with Microsoft Power Automate (or similar workflow automation tools) to orchestrate process automation, notifications, and data movement/integration.
  • Proficiency with Python (or similar scripting languages) for data transformations, automation, API integrations, and lightweight tooling.
  • Understanding of data orchestration and scheduling patterns, including dependency management, retries, and operational runbooks for production pipelines.
  • Experience implementing data quality and observability practices (e.g., validation rules, monitoring/alerting, SLAs) to ensure reliable and trusted datasets.
  • Working knowledge of secure data handling and privacy-by-design principles (e.g., least-privilege access, encryption, PHI/PII considerations) when building and operating data pipelines.
  • Strong SQL experience for data transformation, validation, reconciliation, and performance tuning.
  • Experience with Power BI (data modeling, DAX fundamentals, and performance considerations) to support scalable dashboards and self-serve analytics.
  • Experience working with both structured and unstructured datasets, including file-based or document-oriented data sources.
  • Familiarity with relational and cloud-based data platforms used for analytics and reporting.
  • Experience supporting data migrations, legacy system consolidation, or platform modernization initiatives.
  • Understanding of data quality, documentation practices, and foundational data governance principles.
  • Strong analytical and problem-solving skills, particularly in diagnosing data quality issues and pipeline failures.
  • Ability to collaborate effectively with both technical and non-technical stakeholders, including analytics and AI delivery teams.
  • Strong written and verbal communication skills, with the ability to clearly document data flows, dependencies, and assumptions.

Benefits

  • Health insurance
  • 401(k) matching
  • Flexible work hours
  • Paid time off
  • Remote work options

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