Senior Azure Data Engineer

Full Time
Philippines (Remote)
Posted 1 week ago
7.50 USD / Hour

Website MBVA 24-7

Client: Alumus
Job Title: Senior Azure Data Engineer
Headcount: 1
Basic Hourly Rate: $7.50
Job Type: Full-Time
Work Schedule: Monday – Friday, 8:30 am to 5:00 pm AZ Time

FILIPINO APPLICANTS ONLY

Job Responsibilities:

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.

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.

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.

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.

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.

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.

Governance, Security & Compliance

Enforce data governance standards: cataloging 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.

Job Qualifications:

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.
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, and 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.
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 & modeling
REST and SOAP API design and consumption, OAuth 2.0, JSON/XML parsing, Webhook and event-driven data patterns: API integration
Python (pandas, PySpark, requests, SQLAlchemy) – advanced proficiency required; T-SQL and Spark SQL: Programming Languages
Power BI (including DAX, Power Query, semantic modeling) and 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