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Salary
$87k – $97k per year
Location
Remote (United States)
Employment
Full-Time

Confirmed on the employer's own hiring board on Oct 14, 2026. First seen by Alion on Oct 9, 2026. PointClickCare scores B on the Alion truth index.

Overview
Company
Impact
Profile match
PointClickCare is a Canadian health technology company that provides cloud-based electronic health record and care collaboration software for long-term care, senior living, home health and other post-acute care providers. Its platform covers clinical documentation, billing and revenue management and data exchange with hospitals, health plans and pharmacies, and connects with more than 400 partners through its marketplace. Founded in 2000, it hires software engineers, data analytics engineers and accounts receivable specialists in Canada and the United States. The company is headquartered in Mississauga, Ontario, Canada.

Position Summary:

PointClickCare's Marketing organization is hiring a Marketing Data Analytics Engineer to build and maintain the data infrastructure behind marketing analytics and pipeline reporting. This hands-on, backend-focused role works across Salesforce, Marketo, and the data warehouse, increasingly leveraging AI-assisted analytics tools such as Claude, to streamline how campaign performance data is captured, connected, and reported. The role partners closely with Marketing Analytics, Demand Generation, and Marketing Operations to turn recurring reporting needs into automated, trustworthy data flows that directly support executive-level reporting on marketing-sourced pipeline across the Senior Care and Acute & Payer businesses.

Key Responsibilities:

  • Data Pipelines & Integrations: Design, build, and maintain data pipelines connecting Salesforce, Marketo, and the data warehouse (e.g., BigQuery) to support marketing performance reporting.
  • Reporting Automation & Analytics Enablement: Automate recurring campaign reporting workflows and write/optimize SQL to build reusable datasets, views, and queries that power dashboards and leadership reporting.
  • Campaign Attribution & Data Quality: Strengthen campaign attribution logic (campaign codes, UTM/campaign member data, lead-to-opportunity linkage) and monitor, troubleshoot, and improve data quality across Marketo, Salesforce, and downstream reporting tables.
  • AI-Enabled Analytics Workflows: Apply AI tools such as Claude to accelerate data exploration, documentation, and query development, while maintaining rigor and accuracy in production reporting.
  • Systems Support & Documentation: Support backend administration and configuration in Salesforce and Marketo (fields, objects, sync rules, campaign structures), and document data models, definitions, and processes so metrics stay consistent and self-serve for marketing stakeholders.

Required Skills & Qualifications:

  • Bachelor's degree (completed or in final year) in Software Engineering, Computer Science, Data Engineering, or a related technical field. New graduates are encouraged to apply.
  • 0 - 2 years of applicable experience.
  • Strong SQL skills: comfortable writing joins, aggregations, and window functions against large relational datasets.
  • Working knowledge of at least one programming language used in data work (e.g., Python) for scripting, automation, or ETL.
  • Understanding of relational data models and how CRM/marketing-automation data is structured (leads, contacts, accounts, campaigns, opportunities).
  • Highly analytical and detail-oriented, with a strong bias toward automating repetitive work.
  • Intellectually curious and open-minded, with a genuine thirst to learn new tools, systems, and business context.

Preferred Skills & Experience:

  • Hands-on exposure to Salesforce (SOQL, reports, campaign objects, admin concepts) or Marketo (programs, smart campaigns, field sync).
  • Experience with a cloud data warehouse (BigQuery, Snowflake, Redshift) and BI tools (Power BI, Looker, Tableau).
  • Familiarity with AI-assisted development or analytics tools, such as Claude or similar large language model platforms.
  • Exposure to ETL/ELT tooling, APIs, or workflow orchestration (e.g., dbt, Airflow, Fivetran, or equivalent scripting).
  • Familiarity with marketing funnel metrics (MQLs, opportunities, pipeline) or B2B demand generation.
  • Co-op, internship, or project experience in a data engineering, analytics engineering, or revenue operations context.
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