Data Engineer

Job Description

ALUMUS FAMILY OF COMPANIES

Senior Azure Data Engineer

Data Pipelines • Azure Cloud • APIs & Web Apps • Healthcare Intelligence

Job Title

Senior Azure Data Engineer

Location

Remote – Alumus, Family of Companies (via Deel)

Reports To

Director of Data Management

Employment Type

Full-Time

Industry

Healthcare / Electronic Medical Records

About Alumus

Alumus, Family of Companies is a growing US-based healthcare organization on a mission to improve people’s lives. We integrate with multiple Electronic Medical Record (EMR) systems and operate at the intersection of clinical data, business intelligence, and technology. As we scale, we are building the data infrastructure that will power the next generation of healthcare analytics, reporting, and decision-making .

Role Overview

We are seeking a highly skilled and technically well-rounded Senior Azure Data Engineer who is passionate about data, cloud architecture, and real-world impact. You will own our data pipelines end-to-end, from ingestion and transformation through to the warehouses, matching logic, and reporting layers that clinical and operational teams rely on.

You will work with complex, sensitive healthcare data, integrating information from APIs, Web Applications, EMR systems, and third-party platforms. You will design systems with the future in mind: scalable, clean, and analytically rich. An understanding of data science principles and long-term reporting architecture will set you apart.

A background in healthcare or medical data is advantageous, but far more important is your technical mastery, your ability to think strategically, and your commitment to delivering quality.

Key Responsibilities

1. Azure-Native Data Engineering

• Design, build, and maintain production-grade data pipelines on the Microsoft Azure platform using Azure Data Factory (ADF), Azure Databricks, Azure Synapse Analytics, and related services.
• Architect and manage Azure Data Lake Storage (ADLS Gen2) and Azure SQL Data Warehouse environments with a focus on scalability, performance, and cost efficiency.
• Implement CI/CD pipelines for data infrastructure using Azure DevOps and GitHub Actions.
• Ensure environments follow Azure best practices for security, governance, and compliance - including RBAC, private endpoints, and encryption at rest and in transit.

2. API Integration & Web Application Data Flows

• Design, implement, and maintain robust integrations with RESTful and SOAP APIs, including authentication handling (OAuth 2.0, API keys, JWT), rate-limiting strategies, and error recovery.
• Build and manage data ingestion pipelines that consume data from internal and third-party Web Applications, including real-time and event-driven flows using Azure Event Hubs or Azure Service Bus.
• Develop and maintain Python- or .NET-based microservices and Azure Functions to support lightweight data workflows and API wrappers.
• Monitor API health, data contracts, and schema evolution to proactively prevent pipeline failures downstream.

3. Data Pipelines, Warehousing & Cleanup

• Own the full lifecycle of ETL/ELT pipelines: ingestion, cleansing, validation, deduplication, transformation, and loading into analytical targets.
• Implement sophisticated data matching and entity resolution logic to reconcile patient, provider, and facility records across disparate healthcare systems.
• Design and enforce data quality frameworks - including anomaly detection, completeness checks, and lineage tracking - to ensure trustworthy data at every layer.
• Optimize query performance and storage costs across Azure Synapse, Azure SQL, and Databricks Delta Lake environments.

4. Data Modelling & Warehouse Design

• Design scalable, maintainable data models (dimensional, relational, and lakehouse patterns) that serve both operational reporting and long-term analytical needs.
• Build and manage transformation logic using dbt (Data Build Tool) with full test coverage, documentation, and version control.
• Maintain a clear separation between raw, staging, and curated data layers to support auditability and iterative analytics development.

5. Analytics, Reporting & Data Science Enablement

• Partner with analysts, data scientists, and clinical stakeholders to translate business and clinical questions into robust data products.
• Build reusable, well-documented datasets and semantic layers in Power BI or Azure Analysis Services that support self-service analytics.
• Apply a data science mindset to pipeline design - understanding how downstream ML models, statistical analyses, or predictive tools will consume and depend on your data.
• Contribute to long-term analytics roadmaps: anticipating future reporting needs, designing for extensibility, and proactively surfacing data insights to leadership.

6. Healthcare Data Expertise

• Handle sensitive Protected Health Information (PHI) in compliance with HIPAA and relevant data privacy regulations.
• Integrate with Electronic Medical Record (EMR) systems including HL7 FHIR APIs, HL7 v2 message formats, and proprietary vendor exports.
• Apply domain knowledge (where applicable) to identify data quality issues specific to clinical workflows, coding standards (ICD-10, CPT, SNOMED), and insurance/claims data.

7. Governance, Security & Compliance

• Enforce data governance standards: cataloguing assets in Azure Purview, managing lineage, and maintaining a business glossary.
• Implement and audit access controls, data masking, and audit trails for all sensitive data environments.
• Participate in security reviews and ensure pipelines meet organizational and regulatory compliance requirements.

Qualifications & Requirements

Education

• Bachelor’s degree in Computer Science, Information Technology, Data Engineering, Data Science, or a related field.
• Equivalent practical experience with a demonstrable portfolio of work will be equally considered.

Experience

• 5+ years of experience in a data engineering, analytics engineering, or cloud data architecture role.
• Demonstrable, hands-on experience with the Microsoft Azure data stack (ADF, Synapse, Databricks, ADLS, Azure SQL) - this is a core requirement.
• Proven track record building and maintaining production API integrations and data flows from Web Applications.
• Experience with end-to-end pipeline development: ingestion, transformation, warehousing, and BI layer delivery.
• Healthcare or medical data experience is highly advantageous but not required.

Technical Skills - Required

• Azure Data Factory, Azure Databricks (PySpark), Azure Synapse Analytics, ADLS Gen2, Azure Functions, Azure Event Hubs / Service Bus, Azure DevOps: Azure Platform
• Dimensional modelling, Delta Lake / Lakehouse architecture, dbt, Azure Synapse or Azure SQL: Data Warehousing & Modelling
• REST and SOAP API design and consumption, OAuth 2.0, JSON/XML parsing, Webhook and event-driven data patterns: APIs & Integration
• Python (pandas, PySpark, requests, SQLAlchemy) - advanced proficiency required; T-SQL and Spark SQL: Programming Languages
• Power BI (including DAX, Power Query, semantic modelling), Azure Analysis Services: BI & Reporting
• Data validation frameworks, Azure Purview, data lineage, anomaly detection: Data Quality & Governance
• Git, Azure DevOps pipelines, CI/CD for data infrastructure, Infrastructure as Code (Bicep or Terraform a plus): DevOps & Version Control

Technical Skills - Preferred

• Familiarity with HL7 FHIR, HL7 v2, or healthcare interoperability standards.
• Exposure to data science workflows: feature engineering, model pipelines, or ML-ready dataset design.
• Experience with Azure Machine Learning or integration with AI/ML services.
• Knowledge of Apache Airflow or Azure-native orchestration patterns for complex DAG management.
• Familiarity with Snowflake, dbt Cloud, or multi-cloud data architectures.
• Understanding of HIPAA data handling requirements and healthcare compliance frameworks.

What Sets You Apart

The ideal candidate:

• Thinks architecturally and long-term - you design today’s pipeline knowing where reporting will need to be in 3 years.
• Treats data quality as a core engineering concern, not an afterthought.
• Communicates clearly with non-technical stakeholders - turning complex data questions into actionable solutions.
• Is comfortable across the full data stack: from raw API payloads to polished executive dashboards.
• Understands how analysts and data scientists will use your data and builds with that in mind.
• Takes ownership and maintains clear documentation across all work.

What We Offer

• Fully remote position, globally distributed team.
• Competitive compensation, paid via Deel.
• Work in healthcare technology that directly supports patient care.
• A collaborative environment where engineering contributions are recognized.
• Opportunity to shape data infrastructure from the ground up as we scale.

Alumus, Family of Companies is an equal opportunity employer.