Senior Analytics Engineer

Aquent
United States
2 days ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
7 years minimum
Working hours
Regular working hours
Job source

Tech stack

Sql Data Warehouse Adaptable Database Systems Airflow Business Analytics Applications Data Analysis Cloud Computing Cloud Database Cloud Engineering Cloud Storage Information Systems Continuous Integration Data Architecture
+32 more
Information Engineering Data Governance Extract Transform Load (ETL) Data Mart Data Transformation Data Systems Data Visualization Data Warehousing Dimensional Modeling Data Flow Control Statistical Hypothesis Testing Identity and Access Management Python (Programming Language) Network Security Machine Learning Performance Tuning Cloudera Data Streaming Workflow Management Systems Data Processing Cloud Platform System Sql Optimization Git Data Layers Information Technology Data Lineage Optimization Algorithms Real Time Data Tools for Reporting Stream Processing Software Version Control Data Pipelines

Job description

Aquent, a leading talent solutions company, is partnering with a prominent organization in the financial services sector. This client empowers individuals and institutions with innovative financial tools and insights, leveraging data to drive strategic decisions and enhance customer experiences. As an Aquent talent, you will be instrumental in shaping their data landscape, directly contributing to initiatives that impact critical business operations and future growth. You will embark on an exciting journey to transform raw internal data into trusted datasets, actionable insights, and executive-grade dashboards, taking ownership of the end-to-end analytics stack. This pivotal role offers the chance to modernize their analytics environment, migrate to a cutting-edge cloud platform, and design next-generation data solutions that will directly support operational and strategic decision-making, influencing audiences from frontline teams to senior leadership and board-level stakeholders, thereby fostering a data-driven culture and driving measurable success across the organization.

What You Will Do

  • Drive Data Engineering & Platform Modernization
  • Design, build, and operate robust data pipelines across both legacy and modern cloud platforms, ensuring seamless data flow and integrity.
  • Implement rigorous data quality, lineage, freshness, reliability, and observability practices throughout the entire data lifecycle, especially during critical transitions.
  • Conduct thorough assessments of existing legacy workflows and define optimal target-state architectures leveraging modern cloud services for data transformation, orchestration, and related capabilities.
  • Lead incremental migration efforts, establishing comprehensive validation processes to guarantee functional parity and data accuracy between legacy and modernized workflows.
  • Architect Scalable Data Models & Analytics Solutions
  • Design sophisticated dimensional models, semantic layers, and reusable data marts within the modern cloud data warehouse to support scalable analytics and reporting.
  • Implement industry-leading star-schema and medallion architectures, optimizing for performance and maintainability.
  • Create high-quality, reusable data assets that significantly accelerate dashboard development and empower self-service analytics across the organization.
  • Deliver Production-Grade Dashboards & Business Intelligence
  • Design and deliver compelling production-grade dashboards using leading visualization tools, providing clear and actionable insights.
  • Develop complex data models, advanced calculation expressions, row-level security, intuitive drill-through experiences, and performance optimizations to ensure an exceptional user experience.
  • Publish and govern reporting solutions that deliver executive-ready insights and critical operational visibility to various stakeholders.
  • Generate Transformative Analytics & Insights
  • Perform in-depth trend, cohort, time-series, and comparative analyses to uncover critical business insights and opportunities.
  • Apply hypothesis testing, A/B test analysis, and lightweight predictive techniques to validate assumptions and inform strategic direction.
  • Translate complex data findings into clear, compelling narratives, actionable recommendations, and measurable business outcomes.
  • Proactively identify opportunities to unlock additional value from the organization?s vast data assets, driving innovation and efficiency.
  • Cultivate Strategic Stakeholder Partnerships
  • Serve as a trusted subject matter expert for departmental data and analytics, providing invaluable guidance and expertise.
  • Collaborate closely with business and technical teams to meticulously define requirements, metrics, and reporting needs, ensuring alignment with strategic goals.
  • Efficiently resolve data inquiries and provide accurate, timely analysis to support critical business decisions.
  • Build durable partnerships across various functions, establishing yourself as a trusted advisor who can bridge the gap between data and business strategy.
  • Champion Documentation & Leadership Communication
  • Thoroughly document requirements, data contracts, metric definitions, technical designs, and migration runbooks to ensure clarity and maintainability.
  • Create impactful executive presentations and supporting materials for leadership and board-level discussions, translating complex data into strategic insights.
  • Actively promote reporting standards, advocate for reusable assets, and champion analytics best practices across the entire organization, fostering a data-driven culture.

Requirements

  • 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, or a comparable role, demonstrating leadership responsibilities.
  • Proven hands-on experience developing, maintaining, optimizing, and modernizing legacy data processing workflows.
  • Demonstrated ability to translate 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 Prowess
  • 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 Foundations
  • 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 Acumen
  • Advanced SQL, including complex joins, window functions, CTEs, and cloud data warehouse optimization techniques.
  • Proficiency in Python for analytics, automation, and data transformation.
  • Exceptional Communication Skills
  • Strong written and verbal communication skills.
  • Experience developing executive-level narratives and presentations.
  • Ability to communicate effectively with both technical and non-technical audiences.

Nice-to-Have 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.
  • Working knowledge of R.

About the company

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. We also offer free online training through Aquent Gymnasium. More information on our awesome benefits!

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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