Top Senior Data & Analytics Jobs in Wichita, KS

Supports data modernization by assessing legacy structures, designing modern data architectures, developing ETL/ELT pipelines, integrating APIs and cloud services, and ensuring data quality, security, governance, and lineage. Analyzes data for migration and reconciliation, creates dashboards and reports, and collaborates with technical and business teams. Applies AI tools to improve software development, DevSecOps, testing, security, deployment, and automation processes.

Leads enterprise data-platform architecture for clients using Microsoft Fabric and Azure. Responsibilities include discovery, target-state design, data modeling, migrations, DevOps and CI/CD, governance, security, AI/ML enablement, consulting, pre-sales, technical delivery leadership, mentoring, and development of reusable architecture assets. The role requires hands-on Fabric production experience, enterprise-scale implementation ownership, advanced SQL and Python/PySpark skills, client communication, and travel up to 25%.

Senior Data Manager acquires, validates, integrates, protects, and manages enterprise data throughout its lifecycle. The role develops ETL solutions, data architectures, models, stored procedures, reporting datasets, and visualizations using Databricks, SQL, and cloud technologies. Responsibilities include translating business needs into technical requirements, leading data projects through deployment, analyzing complex data, improving processes, and supporting business decisions through accessible insights.

Designs, builds, tests, and maintains secure, scalable cloud data platforms, pipelines, ETL/ELT processes, data models, data marts, integrations, and reporting services. Supports data migration, archiving, disaster recovery, governance, metadata management, data quality, CI/CD deployments, and performance optimization. Collaborates with architecture, governance, migration, QA, and business teams in an Agile federal environment while maintaining audit-ready documentation and mentoring junior engineers.

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.

Support enterprise asset management data migration and system integration initiatives involving IBM Maximo. Analyze source and target environments, execute migration strategies, develop migration and interface components, validate data exchanged with enterprise platforms, and conduct quality reviews. Coordinate migration workstreams and help implement data governance standards. The role requires Maximo Integration Framework experience, large-scale data management expertise, and eligibility for Public Trust clearance.

Analyze and model marketing, product, and loan application data to optimize the borrower funnel and drive growth. Build BigQuery datasets, dbt models, and Tableau dashboards; evaluate customer behavior, acquisition costs, approval rates, and origination performance. Partner with Product, Marketing, and Engineering on A/B tests, statistical analysis, and actionable insights for leaders. Apply lending and fintech knowledge to improve conversion, customer value, and portfolio outcomes.

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.