Senior Analytics Developer

Conner Strong & Buckelew•Camden, NJ

21h•$95,000 - $110,000•Hybrid

About The Position

The Senior Analytics Developer is responsible for transforming enterprise data into actionable insights through reporting, analytics, visualization, and business intelligence solutions. This role partners with business stakeholders, Information Technology, and Data Analytics teams to deliver trusted data products that support operational efficiency and strategic decision-making. The position will support both traditional business intelligence initiatives and emerging AI-driven analytics capabilities, including document intelligence, knowledge management, and enterprise search solutions. The ideal candidate combines strong analytical thinking with hands-on experience across modern data platforms, visualization tools, Python/ SQL along with low-code applications and information management technologies.

Requirements

Bachelor’s degree in computer science, Information Systems, Data Analytics, Statistics, Business Analytics, or equivalent practical experience.
Minimum 4 years of experience in business intelligence, analytics, reporting, or data-focused solution development.
Demonstrated ability to gather business requirements and independently deliver analytical solutions.
Experience working throughout the full solution lifecycle, including analysis, design, development, testing, deployment, and support.
Strong problem-solving skills with the ability to manage multiple priorities in a fast-paced environment.
Excellent verbal and written communication skills with the ability to explain complex concepts to business users.
Proven ability to learn new technologies and adapt to evolving business needs.
Strong ability to manage multiple initiatives, prioritize work, and deliver within deadlines
Proven ability to rapidly learn and evaluate new platforms and technologies
Strong communication skills with the ability to explain technical solutions to business users
Power BI (semantic models, DAX, Power Query, dashboards, and reporting)
SQL Server, Azure SQL, or similar relational database platforms
Python for data analysis, automation, visualization, or reporting
Power Apps and Power Automate
Microsoft Excel (advanced formulas, Power Query, PivotTables, and data analysis)
SharePoint Online and Microsoft 365
Dataverse and Power Platform data integrations
Data modeling, visualization, and analytical design
API and file-based data integration concepts

Nice To Haves

Microsoft Azure data and analytics services
Microsoft Fabric
Experience supporting enterprise reporting within insurance, employee benefits, healthcare, or financial services organizations
SharePoint-based document management and content repositories
Metadata management, information architecture, and content classification
AI-powered search, document intelligence, and knowledge management solutions
Experience working with unstructured data, OCR outputs, or document extraction platforms
Familiarity with embeddings, vector databases, semantic search etc.
Exposure to enterprise data governance, data catalog, and master data management concepts

Responsibilities

Collaborate with business and technology teams to understand requirements and translate them into reporting, analytical, and data-driven solutions.
Design, develop, and maintain dashboards, scorecards, semantic models, and self-service reporting capabilities.
Create data models, metrics, and key performance indicators that provide consistent and meaningful business insights.
Develop and optimize queries, transformations, and analytical datasets to support reporting and decision-making.
Build Power Apps and workflow solutions that improve business reporting and analytics processes, user experience, and data accessibility.
Integrate and prepare data from multiple business systems, databases, files, APIs, and cloud-based platforms.
Support data quality, validation, reconciliation, and governance activities to ensure confidence in reporting outputs.
Organize, classify, and enrich information stored within enterprise content repositories through metadata and information management practices.
Assist with AI and knowledge-management initiatives by preparing structured and unstructured information for analytics, search, and retrieval solutions.
Create and maintain business glossaries, metric definitions, data dictionaries, and support documentation.
Develop testing plans and coordinate user acceptance testing for reporting and analytics solutions.
Present findings, recommendations, and solution designs to technical and non-technical audiences.
Identify opportunities to improve operational efficiency, reporting automation, and enterprise data utilization.
Provide ongoing support and enhancement of existing analytical solutions through structured management processes.