Sr. Analytics Engineer

Senior Analytics Engineer

The Senior Analytics Engineer is responsible for transforming raw internal data into trusted datasets, actionable insights, and executive-grade dashboards that support operational and strategic decision-making. This role owns the end-to-end analytics stack, including data ingestion, modeling, pipeline engineering, semantic layer development, and dashboard delivery using Tableau and/or Power BI. The Senior Analytics Engineer partners closely with business stakeholders to understand business questions, translate them into scalable data products, and communicate insights effectively to audiences ranging from frontline teams to senior leadership and board-level stakeholders.

Principal Responsibilities:

• Data Engineering & Platform Migration
• Design, build, and operate data pipelines across both the current Alteryx environment and the target BigQuery/GCP platform.
• Ensure data quality, lineage, freshness, reliability, and observability throughout the transition lifecycle.
• Assess existing Alteryx workflows and define target-state architectures using BigQuery, Dataform, dbt, Cloud Composer, and related GCP services.
• Lead incremental migration efforts with validation processes to ensure functional parity between legacy and modernized workflows.

• Data Modeling & Analytics Architecture
• Design dimensional models, semantic layers, and reusable data marts within BigQuery.
• Implement star-schema and medallion (Bronze/Silver/Gold) architectures to support scalable analytics and reporting.
• Create reusable data assets that accelerate dashboard development and self-service analytics.

• Dashboard Development & Business Intelligence
• Design and deliver production-grade dashboards using Tableau and/or Power BI.
• Develop data models, advanced calculations, row-level security, drill-through experiences, and performance optimizations.
• Publish and govern reporting solutions that provide executive-ready insights and operational visibility.

• Analytics & Insight Generation
• Perform trend, cohort, time-series, and comparative analyses to uncover business insights.
• Apply hypothesis testing, A/B test analysis, and lightweight predictive techniques where appropriate.
• Translate data into clear narratives, recommendations, and actionable business outcomes.
• Identify opportunities to unlock additional value from organizational data assets.

• Stakeholder Partnership
• Serve as a subject matter expert for departmental data and analytics.
• Partner with business and technical teams to define requirements, metrics, and reporting needs.
• Resolve data inquiries and support critical business decisions with accurate analysis.
• Build durable partnerships across functions and establish trusted advisor relationships.

• Documentation & Leadership Communication
• Document requirements, data contracts, metric definitions, technical designs, and migration runbooks.
• Create executive presentations and supporting materials for leadership and board-level discussions.
• Promote reporting standards, reusable assets, and analytics best practices across the organization.

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 comparable role with demonstrated leadership responsibilities.
• Hands-on experience developing, maintaining, optimizing, and modernizing Alteryx Designer and Server workflows.
• Proven experience translating complex business problems into scalable analytics solutions and actionable insights.

Google Cloud & BigQuery Expertise:

• Strong experience with BigQuery and the Google Cloud data ecosystem, including several of the following:
• BigQuery (partitioning, clustering, materialized views, authorized views, performance 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 (VPC-SC), and analytics security controls

Business Intelligence & Visualization:

• Extensive experience developing reporting solutions in Tableau and/or Power BI, including:
• Enterprise semantic models and analytics layers
• Advanced Tableau LOD expressions
• Advanced DAX and Power Query (M)
• Interactive dashboards and executive reporting
• Performance optimization strategies
• Governance and deployment through Tableau Server/Online or Power BI Service

Analytics Engineering:

• Strong knowledge of dimensional modeling, star-schema architecture, medallion architecture, data quality frameworks, data lineage, Git-based source control, and CI/CD for analytics and data engineering assets.

Technical Skills:

• Advanced SQL, including complex joins, window functions, CTEs, and BigQuery optimization techniques.
• Proficiency in Python for analytics, automation, and data transformation.
• Working knowledge of R is preferred.

Communication:

• Strong written and verbal communication skills.
• Experience developing executive-level narratives and presentations.
• Ability to communicate effectively with both technical and non-technical audiences.

Preferred Qualifications:

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

Key Deliverables:

• Executive-grade Tableau and/or Power BI dashboards with defined refresh schedules, security controls, and usage monitoring.
• Documented requirements, data contracts, and metric definitions for all engagements.
• Production-ready BigQuery and GCP data pipelines with automated testing, monitoring, and documentation.
• Complete Alteryx-to-GCP migration artifacts, including workflow inventories, target-state designs, re-platformed solutions, validation results, and cutover runbooks.
• Curated and reusable BigQuery datasets with governed semantic layers.
• Insight reports, recommendations, and executive presentations.
• Well-documented SQL, Python, Dataform/dbt, and orchestration code stored in source control.

Success Metrics:

• Timely delivery of high-quality pipelines, dashboards, and analytics solutions.
• Successful execution of Alteryx-to-GCP migration milestones.
• Increased stakeholder adoption of analytics products and self-service reporting.
• Reduced ad hoc reporting requests through reusable analytics assets.
• High pipeline reliability, SLA adherence, and data quality.

"Mindlance is an Equal Opportunity Employer and does not discriminate in employment on the basis of – Minority/Gender/Disability/Religion/LGBTQI/Age/Veterans."