Data Analyst Level III

Diverse Agile Solutions•Menands, NY

About The Position

Data Analyst Level 3 Diverse Agile Solutions (DAS) is seeking an experienced Data Analyst Level 3 to join our team supporting a large-scale data analytics and management initiative. The successful candidate will support COVID-19 data dashboards, data distribution to external entities and the public, and a variety of data management and analytics activities. This is an excellent opportunity for an experienced data professional with strong Python, database, ETL, cloud, and data visualization experience. Position Overview The Data Analyst Level 3 will provide data analysis, data management, reporting, transformation, and visualization support for large-scale data environments. The contractor will work closely with technical teams and stakeholders to research and document technical designs, develop and test programming solutions, troubleshoot and resolve defects, provide technical support, and ensure project deliverables meet established requirements and standards.

Requirements

Bachelor's degree or higher in Data Engineering, Computer Science, Management Information Systems (MIS), Information Technology, or a related field from an accredited institution.
6+ years of experience working on medium- to large-scale technical projects.
6+ years of experience with data analytics , including: Data processing Data transformation Data reporting Data visualization Data analysis
Demonstrated experience ensuring project deliverables and scope are completed and properly documented.
Must be legally authorized to work in the United States .

Nice To Haves

6+ years of experience with Python-based data analytics projects.
6+ years of experience working with relational and NoSQL databases , including technologies such as: Oracle PostgreSQL MongoDB DynamoDB Other enterprise-scale database technologies
Experience working with databases containing 10+ million records .
6+ years of experience developing and maintaining data processing and ETL pipelines.
6+ years of experience developing cloud-native and hybrid applications using serverless platforms.
6+ years of experience designing and implementing data visualizations using large datasets , including datasets containing 1 million+ records .
Experience with analytics and visualization platforms such as Tableau .
Experience working with cloud platforms and cloud-based data services.
Experience supporting public-sector, healthcare, or other highly regulated data environments is a plus.
Strong written and verbal communication skills.
Strong analytical, problem-solving, and troubleshooting skills.

Responsibilities

Perform data analysis and management supporting COVID-19 data dashboards and data distribution initiatives.
Prepare, process, transform, analyze, and report on large and complex datasets.
Support the development and maintenance of data processing and ETL pipelines.
Research, analyze, and document technical requirements and solution designs.
Develop programming solutions to support data analytics and management requirements.
Write and execute unit test plans to validate data processing and application functionality.
Research, troubleshoot, resolve, and test software and data-related defects.
Develop and maintain data transformation and processing workflows.
Support data visualization initiatives involving large datasets.
Develop reports, dashboards, and analytical products for technical and non-technical stakeholders.
Provide customer technical support and assist with troubleshooting data-related issues.
Work collaboratively with other developers, analysts, engineers, project managers, and stakeholders.
Ensure technical deliverables are properly documented and meet project requirements.
Support cloud-native and hybrid data applications and solutions.
Work with relational and NoSQL databases containing large volumes of data.
Assist with data quality, validation, and integrity activities.
Participate in technical discussions, design reviews, testing, and implementation activities.
Perform other related duties as assigned.