Top Senior Data & Analytics Jobs in Birmingham, AL

Develop and maintain Power BI reports, dashboards, visualizations, semantic models, and analytics solutions. Translate business requirements into scalable technical solutions, optimize queries and data models, ensure reporting accuracy and performance, and support data governance. Serve as the primary liaison for business users, provide training and troubleshooting, manage tickets, and collaborate with Data and QA teams. The role also advances AI and machine learning capabilities, mentors colleagues, and contributes to automation, documentation, and code reviews.

Provides senior-level data analysis, compliance reporting, qualitative and quantitative research, business intelligence, dashboards, and program measurement for the Personal Financial Counselor financial disclosure and conflict-of-interest program. Tracks certification, readiness, onboarding, and workforce metrics; identifies trends and risks; develops executive reports and actionable recommendations; supports audit readiness, process improvement, and cross-functional program decision-making.

Build and optimize data transformation pipelines using SQL, dbt, Airflow, Python, BigQuery, and relational databases. Collaborate with stakeholders and data engineers, manage task scheduling, resolve data issues, perform analyses, present recommendations, support data exploration tool adoption, and mentor team members. The role also contributes to hiring, onboarding, and professional development while ensuring data accuracy and insight quality.

Build and operate large-scale audio data pipelines for AI model training. Responsibilities include discovering data sources, improving data-processing systems for quality, throughput, and cost, collaborating with AI scientists, and owning engineering projects through continuous improvement.

Designs and maintains secure, reliable data platforms, including relational data models, migrations, pipelines, monitoring, data quality processes, and self-service reporting access. The role protects PHI and PII through access controls, encryption, audit logging, and governance in a HIPAA environment. It also involves backend API development, code reviews, security reviews, stakeholder collaboration, and mentoring teams on data practices.

Analyze behavioral, transactional, and interaction data to identify fraud patterns and emerging threats. Develop monitoring frameworks, dashboards, and mitigation solutions; evaluate AI fraud-review decisions; and translate findings into prompt, rule, workflow, and machine-learning feature improvements. Collaborate with Fraud Operations and Machine Learning teams, participate in code reviews, and mentor junior analysts. The role requires strong SQL and Python skills, statistical analysis expertise, business judgment, and fraud analytics experience.

Lead analytics support for Fetch’s Food and Beverage vertical, serving as the primary analytics partner for Sales and client stakeholders. Own sub-vertical partnerships, manage analytic capacity, answer senior-level client questions, and guide campaign strategy. Use SQL to manipulate data, develop actionable insights, support QBR storytelling, and communicate recommendations to technical and non-technical audiences. Represent analytics cross-functionally and automate insights using AI-enabled tools.

Analyze Amazon Marketing Cloud, advertising, retail, and commerce data to develop custom queries, reporting, dashboards, tests, forecasts, and actionable client recommendations. Partner with commerce and client teams, explain technical findings, validate data quality, document methodologies, and improve analytics workflows. Support platforms including Amazon, Walmart Connect, and Scintilla while using SQL, BI tools, and optionally Python or R for custom analysis and lightweight modeling.

Own Moxie’s end-to-end data infrastructure, including pipelines, Snowflake warehousing, dbt and Omni modeling, orchestration, observability, and documentation. Partner with Engineering and Finance on schema changes, accounting logic, metrics, and business-critical reporting. Deliver financial or historical EMR data models, establish SOPs and reliability KPIs, optimize performance and cost, and help advance Practice Intelligence toward predictive and prescriptive products with appropriate AI safeguards.

Leads healthcare quality analytics using hospital performance, national rankings, Medicare claims, and CMS data. Replicates quality methodologies, identifies improvement opportunities, builds dashboards and benchmarking tools, and establishes analytic validation standards. Presents insights to executives and customers, supports pre-sales and engagements, partners with data scientists and consultants, and mentors analysts.