Top Remote Analysis Reporting Jobs in Dayton, OH

Leads the integration workstream for an Informatica SaaS MDM implementation. Designs, develops, tests, deploys, and supports batch, real-time, API-based, and event-driven integrations across enterprise systems. Establishes architecture and development standards, manages source-to-target mappings and reconciliation, troubleshoots production pipelines, and ensures governance compliance. Mentors offshore developers, conducts code reviews, and collaborates with business, MDM, data quality, and source-system teams throughout project delivery.

Owns Hagerty’s Qualtrics experience-management platform, including survey programming, contact-list management, deployments, dashboards, and feedback outputs. Analyzes research and survey data to identify themes, develops reports and narratives, presents insights to stakeholders, and supports project timelines and communications. The role also coordinates with internal teams, maintains People Insights resources, and recommends improvements to research and reporting processes.

Designs, builds, operates, and modernizes secure ETL/ELT data pipelines for public health interoperability. Responsibilities include using NiFi, Kafka, Python, and SQL; deploying pipelines on Azure or AWS; implementing CI/CD with GitHub Actions; monitoring with Grafana; troubleshooting production systems; supporting legacy migrations; and ensuring data security, compliance, scalability, and reliability. The role collaborates with architects, integration engineers, data scientists, DevOps/SRE, and product teams.

Designs, develops, and maintains scalable cloud-based data pipelines and enterprise data solutions. The role covers data ingestion, transformation, orchestration, integration, data lakes, cloud warehouses, batch and streaming processes, performance optimization, governance, and lineage. The Senior Data Engineer collaborates with analysts, data scientists, engineers, stakeholders, contractors, and vendors while mentoring junior staff. Core tools include Databricks, dbt, Azure Data Factory, SQL, Python, and Azure.

Executes and monitors scheduled production data and data exchange processes for internal and external customers. Follows and improves SOPs, troubleshoots issues, monitors resolution progress, communicates results, supports outages and patch validation, and balances competing requests. The role requires SQL and Control-M expertise, healthcare technology experience, independent judgment, customer communication, and availability for 24x7 shifts.

Analyze startup user and product data, identify trends and drivers, and turn findings into strategic recommendations. The role owns key metrics and dashboards, leads analytical deep dives, sizes opportunities, evaluates product tradeoffs, supports roadmap prioritization, and develops external-facing insights about startups in partnership with marketing and communications.

Leads New Energy Nexus’s global monitoring, evaluation, and learning function, including theory of change, impact frameworks, indicators, databases, reporting, and organizational learning. Provides technical guidance and capacity building to global chapters and programs, supports fundraising with impact evidence, and partners with Communications and leadership. Oversees knowledge management, data governance, privacy, AI-enabled tools, and impact reporting while ensuring data informs strategy, program improvement, and external communications.

Leads data architecture and engineering modernization across business domains. Designs and implements complex pipelines, integrations, data models, and orchestration using Snowflake, AWS, and Airflow. Establishes data quality, governance, security, testing, observability, CI/CD, and reliability practices. Provides architectural guidance, evaluates technical solutions, leads cross-team initiatives, mentors engineers, and improves platform performance and cost efficiency.

Own the architecture and operation of 9amHealth’s data platform, including Python and SQL ETL/ELT pipelines, AWS infrastructure, Redshift data models, semantic layers, governance, quality, monitoring, and reliability. Establish technical standards, optimize performance and costs, support AI/ML initiatives, build integrations, and mentor data team members. Partner with business and clinical stakeholders to deliver reliable data products and translate complex questions into actionable analytics.

Build and maintain production ETL pipelines for structured and unstructured data, integrate machine learning models for enrichment, develop data transformations and quality monitoring, design warehouses and dimensional models, establish governance frameworks, and contribute to data architecture and platform improvements. Collaborate with data scientists, analysts, and engineering teams to deliver reliable, actionable intelligence.