Top Data & Analytics Jobs

Analyze business operations and complex datasets to identify trends, opportunities, and challenges. Use SQL, statistical methods, hypothesis testing, and Power BI to develop dashboards, executive reports, and actionable recommendations. Translate business requirements into analytical frameworks, design tests measuring incremental growth, collaborate with cross-functional stakeholders, and lead projects from initiation through completion.

Analyzes customer and business requirements, data, test results, and program outputs to implement accurate batch data fulfillment solutions. Serves as a liaison between business, technical, and operational teams; configures systems, executes test plans, troubleshoots processing issues, maintains documentation, and ensures compliance with legal and operational standards. The role also supports process improvements, cost reduction, quality initiatives, and timely program delivery using proprietary systems.

Lead the architecture and development of scalable AWS-based data ingestion, transformation, and orchestration pipelines. Build reliable data infrastructure using Python, SQL, Airflow, Lambda, ECS, SQS, and Terraform. Establish data modeling, quality, lineage, monitoring, testing, and observability practices while partnering with analysts, scientists, and backend engineers. Mentor senior engineers, guide technical decisions, and provide hands-on leadership for complex data platform initiatives.

Design, develop, and maintain Snowflake-based data governance and engineering solutions. Implement Snowflake SQL, ETL, RBAC/ABAC controls, standards, and best practices. Collaborate with stakeholders, present governance practices, author standards, and drive data quality and self-service BI support across Looker/Tableau and FreeWheel platforms.

Build and optimize scalable batch and streaming data pipelines for Comcast’s enterprise Data Lake. Develop cloud-native solutions using AWS, Databricks, PySpark, Kafka, Kubernetes, and Airflow/MWAA. Support high-volume distributed data processing, production troubleshooting, data warehousing, automation, observability, and data quality initiatives. Collaborate with product, governance, analytics, and engineering teams, participate in architecture decisions, mentor junior engineers, and improve platform reliability and performance.

Design and deliver end-to-end web applications and data pipelines that integrate enterprise systems (including Oracle). Build high-performance data models, dashboards (Power BI), REST APIs, and UI components. Integrate tools like Jira and Smartsheet, implement logging/instrumentation (ELK), and collaborate in Agile to provide documentation, training, and ongoing support.

Build and lead Ashley’s consumer insights capability, including research roadmaps, custom qualitative and quantitative studies, insights repositories, prioritization processes, and executive-ready storytelling. Translate consumer, retail, marketplace, feedback, and business data into actionable recommendations for product, marketing, merchandising, pricing, and growth decisions. Influence cross-functional stakeholders, develop AI-enabled synthesis workflows, and manage one direct report while operating resourcefully with imperfect data.

Produces automated and custom client-facing healthcare reports, translating ambiguous business questions into robust analyses and presentations. Builds scalable reporting automation with data engineering partners, improves report efficiency and accuracy, identifies reporting gaps, develops domain expertise, and investigates complex business questions for strategic decision-making. Advocates for strong data visualization, documentation, metric consistency, and stakeholder communication practices.

Manage and transform data exports from legacy POS systems, perform accurate manual data entry, and use tools (Salesforce, Google Sheets, Excel) to support client go-lives and ongoing operations. Be available for scheduled shifts, overtime, and on-call support during implementations.

Design, build, and maintain scalable Databricks-based ETL/ELT pipelines and analytics-ready data products on Azure and on-prem. Partner with business and engineering stakeholders to deliver end-to-end data initiatives, apply enterprise design standards, optimize production pipelines, and present technical solutions to stakeholders.

Design, build, and maintain production-grade ETL/ELT pipelines and analytics-ready data products on Databricks and cloud platforms. Collaborate with data modelers, governance, and cross-functional teams to implement dimensional models, optimize pipeline performance, ensure data quality and support BI consumption, while following Agile/SAFe practices.

As a Data Platform Engineer, you'll architect and implement data services, build data pipelines, optimize for real-time risk assessment, ensure data governance, and collaborate across teams.

Maintain the enterprise fleet ledger and configuration history, build analytical infrastructure and dashboards, produce 6/12/24-month forecasts of availability, and deliver decision-ready briefings to senior leadership.