Top Analysis Reporting Jobs in Albuquerque, NM

Lead data engineer responsible for designing, building, and operating production data pipelines using Python, Airflow, Snowflake, DBT, and AWS. Automate ETL, implement CI/CD, testing and DBT validations, troubleshoot pipelines, and work client-facing to deliver reliable data solutions.

Own growth and player behavior analytics across sportsbook, casino, and poker. Partner with Revenue Ops, Marketing, Product, and VIP to run retention, bonus optimization, segmentation, A/B testing, and predictive modeling using SQL, Snowflake, ML/AI tooling, and Python. Turn analysis into actionable recommendations and measurement frameworks.

Partner with Ads sales to provide data-driven prospecting, reporting, and strategic recommendations. Build SQL queries and dashboards, produce monthly/quarterly client narratives, run incrementality/A-B tests, and present insights to brands. Support new business pitches, automate reporting workflows, and collaborate with Sales, Ad Ops, and Product on ad performance and product testing.

Serve as the analytics bridge between marketing/operations and data teams: translate business questions and KPIs into clear product requirements, own delivery of treated tables, semantic layers, reports and dashboards, align stakeholders on a single source of truth, run gap analyses, document processes, and ensure delivered data products drive decision-making and adoption.

Supervises Data Services team focusing on data engineering and operations, ensuring alignment with IT policies, data governance, and operational reliability of data products.

Lead analytics strategy for client accounts: create measurement plans, testing roadmaps, and cross-channel analyses. Use BI tools and SQL to connect data, generate insights, and present clear, actionable recommendations to clients and internal teams.

Build governed gold-layer data models and a single-source metrics layer in Snowflake (dbt); create and optimize dashboards in enterprise BI tools; use AI coding agents and AI-assisted tooling to accelerate development; ensure data quality, governance, and consistency; collaborate with data engineering and stakeholders to deliver trusted analytics for internal and client-facing use.

Lead enterprise data strategy and governance, build AI-ready data infrastructure and BI systems, own SharePoint platform, partner cross-functionally to ensure data quality, access, compliance, and user adoption.

Design and implement scalable Azure-based data architectures and analytics solutions, lead delivery teams, support pre-sales, drive DevOps/CI-CD, mentor junior staff, define data strategy, governance, migrations, and oversee project delivery and backlog management.

Build and maintain auditable data pipelines in Snowflake and dbt to ensure financial reconciliation and audit readiness. Partner with Accounting, Operations, Engineering, and Reporting to investigate data issues, improve integrations via APIs, and own claim reimbursement and contract sales data workflows.