We are seeking an experienced Senior Data Engineer & Analytics Developer to support the development, management, and analysis of large-scale public health data systems. This role focuses on building and maintaining robust data pipelines, performing advanced analytics, creating dashboards and visualizations, and supporting the distribution of critical health data to internal stakeholders, external agencies, and the public.
The ideal candidate will have expertise in Python, ETL development, cloud-native applications, SQL/NoSQL databases, Tableau, and large-scale data processing. You will work closely with technical teams to deliver scalable, secure, and high-performance data solutions.
Key Responsibilities
Design, develop, and maintain enterprise data pipelines and ETL processes.
Perform data extraction, transformation, validation, and loading from multiple data sources.
Analyze large datasets to identify trends, data quality issues, and actionable insights.
Develop and maintain dashboards, reports, and interactive visualizations.
Design technical solutions for data management and analytics initiatives.
Create and maintain technical documentation, data flow diagrams, and system documentation.
Develop and execute unit tests and validate data processing workflows.
Troubleshoot and resolve complex data and application issues.
Support data integration and distribution to internal systems, external partners, and public-facing platforms.
Optimize database performance and data processing workflows.
Collaborate with business analysts, developers, and technical stakeholders to deliver scalable solutions.
Participate in code reviews, testing, deployment, and production support.
Ensure data accuracy, security, and compliance with organizational standards.
Support cloud-native and hybrid application development using serverless technologies.
Required QualificationsEducation
Bachelor's degree in Data Engineering, Computer Science, Information Systems (MIS), Software Engineering, or a related field from an accredited institution.
Required Experience
Minimum 6 years of experience delivering medium to large-scale technical projects.
6+ years of experience in data analytics, including:
Data processing
Data transformation
Reporting
Data visualization
Experience documenting technical designs and project deliverables.
Experience supporting enterprise data management initiatives.
Experience working through the complete Software Development Life Cycle (SDLC).
Mandatory Technical Skills
Python
SQL
Data Analytics
Data Engineering
ETL Development
Data Transformation
Data Processing
Data Validation
Data Visualization
Reporting
Technical Documentation
Unit Testing
Data Quality Management
SDLC
Performance Optimization
Preferred Qualifications
6+ years of experience developing Python-based data analytics solutions.
Experience working with large-scale relational and NoSQL databases, including:
Oracle
PostgreSQL
MongoDB
DynamoDB
Experience managing datasets exceeding 10 million records.
Experience designing and maintaining enterprise ETL pipelines.
Experience developing cloud-native and hybrid applications using serverless platforms.
Experience designing interactive dashboards using Tableau.
Experience building visualizations for datasets exceeding 1 million records.
Familiarity with AWS or Azure cloud services.
Experience with automated data processing and workflow orchestration.
Preferred Tools & Technologies
Python
Tableau
Oracle Database
PostgreSQL
MongoDB
DynamoDB
SQL
AWS Lambda
Azure Functions
Apache Airflow (Preferred)
Git
REST APIs
JSON
Cloud Storage Services
Soft Skills
Strong analytical and problem-solving abilities.
Excellent attention to detail and data accuracy.
Strong written and verbal communication skills.
Ability to manage multiple priorities in a fast-paced environment.
Collaborative team player with excellent stakeholder management skills.
Strong documentation and organizational skills.

Senior Data Engineer

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