Senior Analytics Engineer

Location: Remote in the Dallas or Denver area
Job Type: Full-Time
Email resumes David Kellogg, Sr. Recruiter, The Judge Group – dkellogg@judge.com

About the Role

Our client, a global financial services company is seeking a Senior Analytics Engineer to transform raw data into trusted datasets, meaningful insights, and executive-level dashboards that drive operational and strategic decision-making. This role owns the end-to-end analytics lifecycle, including data integration, modeling, pipeline development, semantic layer design, and business intelligence reporting.

The ideal candidate will partner closely with business stakeholders to translate complex business questions into scalable analytics solutions and communicate findings to audiences ranging from operational teams to executive leadership.

Our current analytics environment is built on Alteryx and is undergoing a migration to Google Cloud Platform (GCP) and BigQuery. This position will support existing Alteryx workflows while helping design and implement cloud-native analytics solutions.

What You'll Do

Data Engineering & Cloud Migration

• Design, build, and maintain data pipelines across Alteryx and Google Cloud Platform environments.
• Ensure data quality, reliability, lineage, observability, and performance throughout the analytics ecosystem.
• Assess existing Alteryx workflows and design future-state solutions using BigQuery, Dataform, dbt, Cloud Composer, and related GCP services.
• Lead migration efforts from legacy platforms to modern cloud architectures with validation and testing processes.

Data Modeling & Analytics Architecture

• Design and maintain dimensional models, semantic layers, and reusable data marts within BigQuery.
• Implement star schema and medallion (Bronze, Silver, Gold) architectures.
• Develop governed, scalable data assets that support reporting and self-service analytics.

Business Intelligence & Dashboard Development

• Build and maintain enterprise dashboards using Tableau and/or Power BI.
• Develop advanced calculations, row-level security, drill-through functionality, and performance optimizations.
• Deliver executive-ready reporting solutions and operational dashboards.

Analytics & Insights

• Perform trend, cohort, comparative, and time-series analyses.
• Apply hypothesis testing, A/B testing, and predictive analytics techniques when appropriate.
• Translate data findings into actionable business recommendations and compelling narratives.
• Identify opportunities to maximize business value from organizational data assets.

Stakeholder Collaboration

• Serve as a trusted advisor and subject matter expert for analytics and reporting.
• Partner with business leaders and technical teams to define KPIs, metrics, and reporting requirements.
• Support strategic decision-making through accurate analysis and insights.
• Build strong cross-functional relationships across the organization.

Documentation & Leadership Communication

• Document business requirements, technical designs, metric definitions, data contracts, and migration plans.
• Create presentations and analytical materials for executive and board-level audiences.
• Promote analytics best practices, governance standards, and reusable reporting assets.

Required Qualifications

Education

• Bachelor's or Master's degree in Computer Science, Information Systems, Engineering, Statistics, Mathematics, Economics, or a related quantitative field.

Experience

• 7+ years of experience in Analytics Engineering, Data Engineering, Business Intelligence, or a related field.
• Experience leading complex analytics initiatives and projects.
• Hands-on experience developing, maintaining, and optimizing Alteryx Designer and Alteryx Server workflows.
• Proven ability to translate business requirements into scalable analytics solutions.

Google Cloud Platform & BigQuery

Strong experience with BigQuery and the Google Cloud data ecosystem, including several of the following:

• BigQuery (partitioning, clustering, materialized views, authorized views, query optimization, BigQuery ML)
• Cloud Storage
• Dataform and/or dbt
• Cloud Composer (Airflow)
• Cloud Workflows or Cloud Scheduler
• Dataflow, Dataproc, or Pub/Sub
• IAM, VPC Service Controls, and analytics security frameworks

Business Intelligence

Experience with Tableau and/or Power BI, including:

• Enterprise semantic models and analytics layers
• Tableau Level of Detail (LOD) expressions
• DAX and Power Query (M)
• Interactive dashboards and executive reporting
• Performance tuning and optimization
• Tableau Server/Online or Power BI Service deployment and governance

Technical Skills

• Advanced SQL, including complex joins, CTEs, window functions, and query optimization.
• Strong knowledge of dimensional modeling and analytics engineering best practices.
• Experience with data quality frameworks, data lineage, Git-based version control, and CI/CD processes.
• Proficiency in Python for analytics, automation, and data transformation.
• Working knowledge of R preferred.

Communication Skills

• Strong verbal and written communication skills.
• Experience presenting insights to executive audiences.
• Ability to communicate effectively with both technical and non-technical stakeholders.

Preferred Qualifications

• Experience migrating from Alteryx, SSIS, Informatica, or other legacy ETL platforms to cloud-native solutions.
• Google Cloud Professional Data Engineer or Associate Cloud Engineer certification.
• Experience with Looker or Looker Studio.
• Knowledge of streaming and near real-time data architectures using Pub/Sub and Dataflow.
• Experience with data governance platforms such as Dataplex, Collibra, Microsoft Purview, or Alation.
• Experience with predictive analytics, forecasting, anomaly detection, and segmentation techniques.
• Background in financial services, wealth management, banking, or other highly regulated industries.
• Tableau Certified Data Analyst and/or Microsoft PL-300 certification.

Key Deliverables

• Executive-level Tableau and/or Power BI dashboards with governance, security, and monitoring in place.
• Documented requirements, metrics, and data definitions.
• Production-ready BigQuery and GCP data pipelines with testing and monitoring.
• Successful migration of Alteryx workflows to cloud-native architectures.
• Curated and reusable BigQuery datasets and semantic layers.
• Insight reports, business recommendations, and executive presentations.
• Well-documented SQL, Python, Dataform/dbt, and orchestration code managed in source control.

Success Measures

• On-time delivery of high-quality analytics solutions, dashboards, and data pipelines.
• Successful execution of Alteryx-to-GCP migration initiatives.
• Increased business adoption of analytics and self-service reporting capabilities.
• Reduction in manual and ad hoc reporting requests through reusable data products.
• High data quality, reliability, and SLA performance across analytics platforms.

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