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Senior Analytics Engineer

Skill
sick time
United States, Texas, Southlake
Jul 29, 2026
Overview

Placement Type:

Temporary

Salary:

$78.03-86.67 Hourly

W2

Start Date:

Aug 17, 2026

Aquent, a leading talent solutions company, is partnering with a prominent organization in the financial services sector dedicated to empowering individuals and institutions with innovative financial tools and insights. This client is at the forefront of leveraging data to drive strategic decisions and enhance customer experiences. As an Aquent talent, you will play a pivotal role in shaping their data landscape, contributing directly to initiatives that impact critical business operations and future growth.

We are seeking a highly skilled and motivated professional to join our client's team, where you will transform raw internal data into trusted datasets, actionable insights, and executive-grade dashboards. This is an exceptional opportunity to own the end-to-end analytics stack, from data ingestion and modeling to pipeline engineering, semantic layer development, and dashboard delivery. You will be instrumental in migrating their analytics environment from a legacy system to a modern cloud platform, designing and building the next generation of data solutions. Your work will directly support operational and strategic decision-making, influencing audiences from frontline teams to senior leadership and board-level stakeholders. This role offers the chance to make a significant impact by delivering robust data products and fostering a data-driven culture.

What You Will Do




  • Data Engineering & Platform Migration



    • Design, build, and operate data pipelines across both the current legacy environment and the target modern cloud platform.
    • Ensure data quality, lineage, freshness, reliability, and observability throughout the transition lifecycle.
    • Assess existing legacy workflows and define target-state architectures using modern cloud services for data transformation, orchestration, and related cloud 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 the modern cloud data warehouse.
    • 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 leading visualization tools.
    • 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 legacy data processing workflows.
    • Proven experience translating complex business problems into scalable analytics solutions and actionable insights.



  • Cloud Data Ecosystem Expertise



    • Strong experience with a leading cloud data warehouse and its associated cloud data ecosystem, including several of the following:
    • Cloud data warehousing (partitioning, clustering, materialized views, authorized views, performance optimization, in-warehouse machine learning capabilities)
    • Cloud Storage
    • Data transformation tools (e.g., Dataform and/or dbt)
    • Workflow orchestration (e.g., Cloud Composer/Airflow)
    • Scheduling services (e.g., Cloud Workflows or Cloud Scheduler)
    • Data processing services (e.g., Dataflow, Dataproc, or Pub/Sub)
    • Identity and Access Management, network security controls, and analytics security controls



  • Business Intelligence & Visualization



    • Extensive experience developing reporting solutions in leading visualization platforms, including:
    • Enterprise semantic models and analytics layers
    • Advanced calculation expressions in visualization tools
    • Interactive dashboards and executive reporting
    • Performance optimization strategies
    • Governance and deployment through enterprise visualization services



  • 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 cloud data warehouse 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 legacy ETL platforms to cloud-native architectures.
  • Relevant professional cloud data engineering or associate cloud engineer certification.
  • Experience with other leading data visualization or business intelligence tools.
  • Familiarity with streaming and near-real-time data architectures using messaging and stream processing services.
  • Experience with data governance and catalog platforms.
  • Knowledge of applied predictive analytics, forecasting, anomaly detection, and segmentation techniques.
  • Experience within financial services, wealth management, or other regulated industries.
  • Relevant professional data analyst certification.


Key Deliverables



  • Executive-grade dashboards from leading visualization tools with defined refresh schedules, security controls, and usage monitoring.
  • Documented requirements, data contracts, and metric definitions for all engagements.
  • Production-ready cloud data pipelines with automated testing, monitoring, and documentation.
  • Complete legacy-to-cloud migration artifacts, including workflow inventories, target-state designs, re-platformed solutions, validation results, and cutover runbooks.
  • Curated and reusable cloud data warehouse datasets with governed semantic layers.
  • Insight reports, recommendations, and executive presentations.
  • Well-documented SQL, Python, data transformation tool code, and orchestration code stored in source control.


Success Metrics



  • Timely delivery of high-quality pipelines, dashboards, and analytics solutions.
  • Successful execution of legacy-to-cloud 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.


Please note: This position is available on a W-2 employment basis only and is not open to Corp-to-Corp (C2C) arrangements. The client is also unable to provide employment-based visa sponsorship or transfers for this role.

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About Aquent Talent:

Aquent Talent connects the best talent in marketing, creative, and design with the world's biggest brands.

Our eligible talent get access to amazing benefits like subsidized health, vision, and dental plans, paid sick leave, and retirement plans with a match.

Aquent is an equal-opportunity employer. We evaluate qualified applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, and other legally protected characteristics. We're about creating an inclusive environment-one where different backgrounds, experiences, and perspectives are valued, and everyone can contribute, grow their careers, and thrive.

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