AI-Data Scientist Expert / Sr. Analytics Engineer - Remote

As an AI-Data Scientist Expert / Sr. Analytics Engineer, you will be responsible for designing, modernizing, and managing enterprise analytics platforms that transform raw data into trusted datasets, actionable insights, and executive-level reporting. You will own the end-to-end analytics lifecycle, including data engineering, analytics architecture, data modeling, business intelligence, cloud migration, and advanced analytics initiatives. This role requires deep expertise in analytics engineering, cloud data platforms, dashboard development, and stakeholder engagement, with a focus on migrating legacy analytics workflows to a modern Google Cloud Platform (GCP) and BigQuery ecosystem while delivering scalable and business-driven data solutions., * Design, build, and maintain enterprise data pipelines across legacy and cloud-native analytics environments.

• Lead the migration of analytics workflows, data models, and reporting solutions to Google Cloud Platform and BigQuery.
• Assess existing ETL and analytics processes and define scalable target-state architectures.
• Design and implement robust data quality, observability, lineage, governance, and validation processes.
• Develop dimensional data models, semantic layers, and reusable data marts to support enterprise analytics.
• Implement star-schema and medallion architecture patterns for scalable analytics and reporting solutions.
• Create reusable analytics assets that accelerate self-service reporting and dashboard development.
• Design, develop, and support executive-grade dashboards using Tableau and/or Power BI.
• Build advanced calculations, security models, drill-through functionality, and optimized reporting experiences.
• Publish and govern business intelligence solutions that provide operational visibility and strategic insights.
• Perform advanced data analysis including trend analysis, cohort analysis, time-series analysis, and comparative analytics.
• Apply statistical methods, hypothesis testing, predictive analytics, forecasting, and business performance measurements where appropriate.
• Translate complex analytical findings into actionable recommendations and business narratives.
• Partner with business and technical stakeholders to define requirements, metrics, KPIs, and reporting objectives.
• Provide subject matter expertise in analytics, data engineering, and business intelligence.
• Support critical business decisions with accurate analysis and executive-level reporting.
• Document requirements, data contracts, metric definitions, technical designs, migration plans, and operational runbooks.
• Create presentations, reports, and executive communications for leadership and stakeholder audiences.
• Establish analytics standards, governance practices, reusable frameworks, and best practices across the organization.
• Ensure analytics assets are scalable, secure, maintainable, and aligned with strategic business goals.

• Bachelor's or Master's degree in Computer Science, Information Systems, Engineering, Statistics, Mathematics, Economics, or a related quantitative field.
• 7+ years of experience in Analytics Engineering, Data Engineering, Business Intelligence, Data Science, or related roles.
• Proven experience designing and implementing enterprise analytics and data engineering solutions.
• Hands-on experience developing, optimizing, and modernizing Alteryx Designer and Alteryx Server workflows.
• Strong expertise translating complex business problems into scalable analytics and reporting solutions.
• Extensive experience with Google BigQuery and the Google Cloud data ecosystem.
• Experience with BigQuery partitioning, clustering, materialized views, authorized views, performance tuning, and BigQuery ML.
• Experience with Google Cloud Storage and cloud-native data architecture.
• Strong experience with Dataform, dbt, or similar data transformation frameworks.
• Experience with Cloud Composer (Airflow), workflow orchestration, and scheduling solutions.
• Knowledge of Dataflow, Dataproc, Pub/Sub, Cloud Workflows, and Cloud Scheduler.
• Experience implementing IAM, VPC Service Controls, and analytics security practices.
• Expertise in dimensional modeling, star-schema design, and medallion architecture frameworks.
• Strong knowledge of data quality, data lineage, metadata management, and data governance principles.
• Experience utilizing Git-based source control and CI/CD practices for analytics and data engineering assets.
• Advanced SQL expertise including complex joins, CTEs, window functions, query optimization, and performance tuning.
• Strong Python programming skills for analytics, automation, ETL, and data transformation development.
• Extensive experience designing and developing enterprise reporting solutions using Tableau and/or Power BI.
• Experience creating semantic layers, advanced Tableau calculations, LOD expressions, DAX measures, and Power Query transformations.
• Experience developing executive dashboards, self-service analytics platforms, and operational reporting solutions.
• Strong analytical, problem-solving, and data storytelling capabilities.
• Experience creating executive presentations and communicating insights to senior leadership.
• Excellent verbal and written communication skills with the ability to engage both technical and business audiences.
• Ability to lead initiatives independently and collaborate effectively across cross-functional teams.
• Experience migrating from legacy ETL platforms such as Alteryx, SSIS, or Informatica to cloud-native architectures preferred.
• Google Cloud Professional Data Engineer or Associate Cloud Engineer certification preferred.
• Experience with Looker or Looker Studio preferred.
• Knowledge of streaming and near-real-time data architectures using Pub/Sub and Dataflow preferred.
• Experience with data governance and catalog platforms such as Dataplex, Collibra, Microsoft Purview, or Alation preferred.
• Experience applying predictive analytics, anomaly detection, forecasting, and customer segmentation techniques preferred.
• Experience within financial services, wealth management, or other regulated industries preferred.
• Tableau Certified Data Analyst and/or Microsoft PL-300 certification preferred.
• Working knowledge of R programming preferred.