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Health Monitor Network

Senior Data Engineer & Power BI Developer

Health Monitor Network · $100K–$130K/yr

Advertising Services · 51-200 employees

Jul 30
Senior (5-10 yrs) Full-time
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About the role

The role involves end-to-end management of the data platform, including building ETL pipelines, integrating APIs, and maintaining data architecture. Additionally, the engineer will develop Power BI dashboards and collaborate with business units to translate data into actionable insights.

What they look for

Data Engineering Python SQL Power BI ETL Pipelines API Integration Data Modeling BigQuery DAX Power Query NetSuite Salesforce Data Architecture Data Quality Cloud Computing Business Intelligence

Requirements

Candidates must have 5-7 years of experience in data engineering or analytics with proficiency in Python, advanced SQL, and Power BI. A bachelor's degree in a technical field is required, along with experience in data modeling and working with ERP/CRM systems.

Full description

Company Overview

For over 40 years, Health Monitor has been a nationally recognized, targeted healthcare marketing platform for the Pharma/OTC industry. Our in-house, award-winning content studio creates bespoke healthcare education that fosters more productive patient-physician dialogues at every point of care—we call it #TheHealthMonitorDifference. We have the largest proprietary physician office network in the industry, with over 250,000 offices and more than 450,000 healthcare professionals engaging with our omnichannel educational products. Health Monitor delivers premium point of care content that empowers patients and HCPs with trusted information to achieve the best health outcomes while driving impactful ROI for brands.

Learn more at healthmonitornetwork.com and follow us on LinkedIn, X, YouTube and Instagram.

Position Overview

The Senior Data & Analytics Engineer owns our data platform end to end—from source systems through the dashboards our business runs on. This is a hybrid role: the majority of the work is building and operating reliable data pipelines, integrating APIs, and modeling data within our environment; the remainder is building the Power BI dashboards and business partnerships that turn that data into decisions. You'll work closely with Finance, Operations, Sales, and Marketing to make sure the data behind every dashboard is accurate, trusted, and answering the right question.

Essential Job Functions

Data Engineering (majority of the role)

  • Build & operate ETL pipelines — design and maintain scalable pipelines that move data from source systems through transformation into analytics-ready datasets.
  • Python scripting & orchestration — own and improve the Python-based ingestion behind scheduled loads, adding retries, logging, and moving toward proper orchestration.
  • API integrations & JSON — integrate internal and third-party APIs, handling pagination, rate limits, retries, and schema drift; parse and normalize nested JSON into structured tables.
  • Data modeling & architecture — maintain the layered warehouse (raw landing → transformed → reporting) and deliver clean, documented datasets optimized for BI.
  • Quality & observability — implement data-quality checks and monitoring/alerting (e.g., freshness and failure alerts to Teams) so issues are caught before stakeholders notice.

Analytics & Business Intelligence

  • Build Power BI dashboards — develop and maintain dashboards on the curated reporting layer, using DAX, Power Query, modeling, and visual best practices.
  • Understand the business problem — partner with Finance, Operations, Sales, and Marketing to translate ambiguous questions into well-defined metrics and the right data to support them.
  • Tell the story — turn data into clear, usable insight — not just charts, but answers.

Required Qualifications

Core must-haves

  • ETL pipeline management — building and operating production pipelines and data architectures.
  • Python scripting — for data transformation, automation, API integration, and pipeline development.
  • API integrations & JSON — integrating API-based sources and nested JSON into ETL workflows.
  • Data modeling & architecture — relational databases and analytics-focused modeling, including layered warehouse design.
  • Bachelor's Degree in Computer Science, Data, Science, Information Systems/Information Technology, or a related technical field required. Equivalent practical experience will also be considered.
  • 5-7 years in data engineering, analytics engineering, or a related field.
  • Advanced SQL (BigQuery preferred).
  • Power BI — DAX, Power Query, data modeling — able to build and maintain dashboards independently.
  • Experience with NetSuite (ERP) and Salesforce (CRM) data.
  • Strong problem-solving, a business-first mindset, and clear communication with cross-functional stakeholders.

Preferred Qualifications

  • AI platforms & tooling — hands-on experience using AI/LLM platforms to accelerate data and analytics work; experience with Claude (Anthropic) a plus.
  • Orchestration — Dagster or Apache Airflow.
  • GCP — BigQuery, Cloud Storage, Compute Engine; exposure to Snowflake / Redshift / AWS.
  • Modern dev workflow — GitHub, code review, CI/CD; AI-assisted coding tools (e.g., GitHub Copilot, Claude Code).

ADA – Physical Demands (Office Position)

While performing the duties of this job, the employee is frequently required to sit; use hands to finger, handle, or feel objects, tools, or controls; talk and hear. The employee frequently uses a computer keyboard and views computer monitors for extended periods. Specific vision abilities required by this job include close vision and the ability to adjust focus.