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Data Generalist (USA/Canada, Part time, Remote)

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<strong>Job Description<br><br></strong>We are seeking a <strong><strong>senior, part-time Data Generalist</strong></strong> to support analytics, data engineering, and MarTech initiatives over a <strong><strong>4-month contract (March–June)</strong></strong>. This project may extend beyond that, but that is what we anticipate right now. This role is ideal for a highly autonomous engineer who can operate with minimal handholding in a fast-moving environment.<br><br>The role is remote, based in North America, averaging ~15 hours per week, with workload that may be uneven or “spiky” depending on project needs. Strong communication and comfort in client-facing discussions are essential.<br><br><strong>Responsibilities<br><br></strong><ul><li>Design, build, and optimize data pipelines and analytics solutions on Google Cloud Platform (GCP).</li><li>Develop and optimize BigQuery datasets using partitioning, clustering, and query optimization.</li><li>Build and maintain ETL/ELT pipelines using Python, SQL, and tools such as Fivetran and dbt.</li><li>Develop and support custom APIs using Cloud Functions or Cloud Run.</li><li>Implement event-driven architectures using Pub/Sub and workflow orchestration via Cloud Composer (Airflow) or Cloud Workflows.</li><li>Apply IAM and security best practices, including handling PHI/PII in HIPAA-compliant environments.</li><li>Support marketing data use cases including attribution, Google Ads, Meta Ads, and API-based integrations.</li><li>Partner closely with the Martech Architect to translate business and marketing requirements into scalable technical solutions.</li><li>Communicate clearly with internal teams and clients, explaining technical concepts and tradeoffs.<br><br></li></ul><strong>Requirements<br><br></strong><strong><strong>Must-Have<br><br></strong></strong><ul><li>Strong expertise in Google Cloud Platform, including:</li><li></li><ul><li>BigQuery (partitioning, clustering, optimization)</li><li>Cloud Functions and/or Cloud Run</li><li>Pub/Sub</li><li>IAM and security best practices</li><li>Cloud Composer (Airflow) or Cloud Workflows</li></ul><li>Solid data engineering background, including:</li><li></li><ul><li>Python (pandas, requests, google-cloud libraries)</li><li>Advanced SQL (complex queries, window functions, performance tuning)</li><li>ETL/ELT pipeline design</li><li>Data modeling (star and snowflake schemas)</li><li>Familiarity with dbt</li><li>Experience with data clean rooms</li></ul><li>Experience in healthcare and/or marketing technology, including:</li><li></li><ul><li>HIPAA compliance requirements</li><li>PHI/PII handling</li><li>Marketing attribution concepts</li><li>API integrations (REST, OAuth)</li></ul><li>Hands-on experience with:</li><li></li><ul><li>Fivetran</li><li>Git version control</li><li>Terraform (infrastructure as code)</li><li>Monitoring tools (Datadog, Cloud Monitoring)</li><li>Analytics platforms such as Tableau or Looker</li></ul><li>Strong written and verbal communication skills; comfortable working directly with clients.</li><li>Ability to work independently with limited oversight; senior-level judgment and execution.<br><br></li></ul><strong><strong>Nice-to-Have<br><br></strong></strong><ul><li>Experience with LiveRamp or IQVIA</li><li>Prior healthcare data background</li><li>Backend development experience using JavaScript/TypeScript<br><br></li></ul>

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Common Interview Questions And Answers

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