Top Remote Analysis Reporting Jobs in Houston, TX

Analyzes branch, regional, and national performance data to identify trends, root causes, and opportunities that improve sales effectiveness, conversion, product penetration, and productivity. Develops dashboards, executive reporting, KPIs, and data stories; evaluates initiatives and campaigns; ensures data integrity; and partners with sales, product, field execution, and analytics teams to deliver actionable recommendations and support business decisions.

Leads Citizens’ enterprise semantic analytics strategy and AtScale-based semantic layer operating model. Establishes governed, auditable processes for requirements, metric definitions, modeling, validation, certification, deployment, and change management. Oversees BI platform strategy across Power BI, Tableau, Alteryx, and WebFOCUS, while driving natural language query capabilities, business adoption, partner delivery, executive governance, and distributed team leadership.

Manage Epic Cogito reporting projects for healthcare organizations by gathering requirements, designing and developing reports, performing testing and validation, and providing post-implementation support. Collaborate with internal and external stakeholders, solve complex problems, and manage multiple projects independently while delivering healthcare IT and analytics solutions.

The Director of Biostatistics leads statistical strategy and analysis for clinical trials in oncology, collaborating with clinical teams and regulatory bodies.

Supports value-based healthcare programs through complex SQL analysis, reporting, data reconciliation, program evaluation, payment support, and ad hoc analytics. Works with healthcare and insurance data, develops monthly reports, evaluates new opportunities, and communicates findings to senior and executive leadership. The role requires advanced Excel and large-scale data experience, with preferred expertise in Azure Synapse Analytics, Databricks, PySpark, or Python.

Leads a team of 5–8 data engineers and analysts while remaining hands-on with Databricks and Azure data platforms. Owns scalable pipelines, Lakehouse architecture, data products, quality, governance, reliability, security, and cost management. Oversees hiring, coaching, performance, delivery prioritization, agile execution, production health, incident response, stakeholder communication, and cross-team collaboration. Helps shape global data engineering strategy, standards, technology adoption, and platform evolution.

Analyze merchant and product data to create business cases, pricing models, ROI analyses, reporting, and financial narratives. Partner with Sales, Merchant Success, Product, and Engineering to support merchant acquisition, expansion, renewals, product improvements, and roadmap development. Engage directly with consumer brands to understand reporting needs and communicate complex insights to technical and non-technical audiences.

Supports the Product Innovation Team by modifying and optimizing SQL queries, visualizing data with BI tools, identifying insights, and analyzing enhancements. Participates in coding, testing, documentation, and discussions while providing customer service and managing multiple tasks. The internship requires at least 30 hours per week and emphasizes advanced Excel and visualization skills, plus familiarity with Python and SQL.

Build and maintain FinOps data pipelines, BigQuery and dbt models, cost attribution systems, forecasting and anomaly detection models, and cost-versus-revenue analytics. Identify and implement AWS and GCP savings opportunities, automate governance with Python, Terraform, and Lambda, and partner with Engineering, Finance, Product, and leadership on cloud costs, forecasting, reporting, and architecture decisions.

Designs, builds, and maintains scalable ETL and data processing pipelines supporting analytics, forecasting, risk, and customer insights. Leads complex SQL development, data modeling, governance, quality, lineage, security, and compliance. Partners with engineering, finance, sales, compliance, product, analysts, and data scientists to translate requirements into reliable workflows. Evaluates emerging technologies, leads proof-of-concepts, and develops automated solutions using Python, Spark, Databricks, cloud platforms, orchestration tools, and modern data warehouses.

Transforms complex retail and consumer data into business-ready datasets, scalable pipelines, reporting solutions, automation, and client deliverables. Designs data integration solutions in Unify, troubleshoots connector issues, explores AI-driven improvements, and partners with Product, Engineering, Client Development, Operations, and business stakeholders to define requirements and deliver scalable solutions.