Top Entry Level Analysis Reporting Jobs in Dallas, TX

Participate in a rotational analyst development program focused on using data and technology to analyze performance trends, identify business opportunities, and support strategic decisions in the insurance industry. Build analytical, technical, business, and communication skills through training, mentorship, and rotational assignments. Use tools such as Excel, SQL, Python, R, SAS, Snowflake, Power BI, and emerging AI technologies.

Migrates customer data from legacy and competitor systems into SaaS products using SQL-based tools. Performs extraction, transformation, cleanup, validation, auditing, data mapping, and quality assurance. Develops repeatable scripts and workflows, collaborates with customers and cross-functional teams, supports testing and defect resolution, and documents migration processes. The role increasingly uses BigQuery, cloud platforms, automation, and intelligent tools while supporting global delivery across regions and time zones.

Leads executive-facing analytics for Home Lending Product Strategy, framing hypotheses, measuring impact, evaluating tradeoffs, and delivering recommendations and business cases. Coordinates analysts across matrixed teams, partners with Strategy, Product, Marketing, Finance, Originations, and Technology, conducts market and competitor research, and translates complex analysis into concise insights for senior decision-makers.

Analyzes web and mobile customer journeys, funnels, feature adoption, campaigns, and digital performance. Builds dashboards, defines KPIs, validates tracking, investigates data discrepancies, and evaluates A/B tests. Provides technical support for customer portals, partners with developers on tag management and data layers, maintains measurement documentation, and delivers actionable recommendations to technical and non-technical stakeholders while supporting privacy, accessibility, consent, and regulatory requirements.

Build and maintain SQL-based data models, transformations, pipelines, dashboards, and reports. Validate data accuracy, investigate discrepancies, monitor data quality, document provenance, and test pipelines under realistic conditions. Translate business needs into technical requirements, support ad hoc analysis, and collaborate with analysts, engineers, product partners, and stakeholders. The role includes mentorship and opportunities to develop expertise in end-to-end dataset ownership, Python automation, cloud data warehouses, and transformation tools.

Leads enterprise data governance execution and manages a team responsible for data stewardship, quality, controls, privacy, records management, and remediation. Partners with business, Technology, Risk, Compliance, Audit, and Operations stakeholders to prioritize work, manage capacity, resolve data risks, maintain lifecycle documentation, monitor quality metrics, and ensure data meets business and regulatory requirements. Drives process improvement, accountability, stakeholder communication, and people development.

Reviews annotated sensor and map data for quality, identifies recurring issues, and recommends solutions. The role prepares reports, maintains annotation policies, develops training documentation, performs data annotation, tests internal tools, reports bugs, and creates visual assets. It also collaborates with stakeholders, partners, annotators, project managers, and engineers while supporting on-road operations and evolving program priorities.

Designs, integrates, and manages scalable batch and streaming data pipelines from internal and external sources. Responsibilities include data transformation, schema and business-rule enhancements, load monitoring, troubleshooting data availability, evaluating emerging technologies, and collaborating with business, engineering, and privacy teams. The role also supports data governance, secure data handling, cloud technologies, and adoption of AI-enabled tools.

Designs and optimizes data architectures, pipelines, databases, and Big Data solutions. The role develops partitioning and indexing strategies, supports scalable and secure data infrastructure, documents enterprise data standards, and collaborates with architects, engineers, product teams, and business stakeholders. Responsibilities include database performance tuning, distributed systems development, data modeling, and alignment with Agile delivery practices.

Develops automated reporting, forecasting tools, SQL queries, Power BI dashboards, and analytical solutions. Partners with managers and departments to identify data-driven opportunities, analyze large datasets, define performance metrics, and improve decision-making. Tests and refines reporting tools for accuracy, usability, reliability, and long-term business value.