Top Senior Data & Analytics Jobs

Leads business analysis across customer acquisition and lifecycle experience analytics. The role evaluates funnels, customer behavior, segmentation, CAC, LTV, retention, experimentation, and forecasting; builds dashboards and reporting; translates complex data into growth strategies; partners cross-functionally with marketing, product, data, customer, risk, and engineering teams; and manages and mentors analysts.

Designs and delivers governed Power BI datasets, dashboards, and analytics solutions across a healthcare system. Develops scalable Snowflake data models, maintains metric definitions and metadata in Alation, resolves data quality issues, and translates stakeholder needs into actionable insights. Leads medium to large initiatives, coordinates dependencies, mentors junior developers, improves analytics standards, and collaborates with engineering and data science teams. The role requires Epic Cogito certification and supports clinical, business, finance, HR, legal, and compliance analytics.

Analyze customer lifecycle and Customer Success data to measure attribution, campaign performance, product adoption, retention, and revenue impact. Build multi-touch attribution models, integrate digital engagement data with Gainsight and CRM events, clean and unify datasets, segment audiences, identify journey bottlenecks, and create Tableau or Looker dashboards. Partner with Campaign Strategy, Product Insights, and CS Operations teams to deliver actionable recommendations and improve automated and human customer interventions.

Builds and maintains Power BI reports, dashboards, apps, semantic models, and data transformations for business functions. Partners with stakeholders to define requirements and KPIs, manages Power BI Service administration, configures data refreshes and gateways, validates data, leads testing, tunes performance, trains users, and supports Power Platform governance and documentation.

Own analytics for Blue Origin’s MES/QMS technology suite, using data engineering, analysis, dashboards, visualization, and storytelling to guide product and business decisions. Build QA and testing pipelines, ensure data accuracy and freshness, drive technology adoption, assess product impact, and influence executive strategy. The role requires expertise in SQL, BI tools, Python, cloud and big data technologies, plus manufacturing, operations, supply chain, or aerospace analytics experience.

Leads the architecture, development, and delivery of enterprise data platforms using Snowflake, AWS, Python, Spark, Informatica, and modern ELT frameworks. Designs Data Vault and dimensional models, scalable ingestion pipelines, and cloud data architectures. Provides technical leadership, mentors engineers, manages delivery across initiatives, and ensures data quality, performance, governance, monitoring, and production reliability. Partners with business and technical stakeholders to translate requirements into robust data solutions.

Lead design and implementation of tracking with GTM, analyze user behavior in GA4, build BigQuery queries and dashboards, define KPIs with cross-functional teams, troubleshoot tagging/data issues, and perform deep-dive conversion and journey analyses to optimize web and mobile performance.

Analyzes unstructured customer feedback using text analytics, NLP, LLMs, SQL, Python/R, and BigQuery to identify sentiment, root causes, trends, and customer experience opportunities. Owns feedback taxonomies, models, workflows, and validation standards; connects feedback with behavioral and operational data; delivers business recommendations and executive storytelling; partners cross-functionally on measurement strategy and roadmaps; and mentors junior analysts.

Design, build, and operate high-throughput Go services and data pipelines powering a cybersecurity data lake. Own bronze, silver, and gold layers, including ingestion, enrichment, partitioning, compaction, schema evolution, and performance optimization. Translate threat intelligence workflows into reliable production systems, collaborate across teams, participate in on-call operations, and mentor engineers. The role requires distributed-systems expertise, experience with open table and columnar formats, object storage, ClickHouse, PostgreSQL, and large-scale datasets.

Designs, implements, and maintains secure, scalable ETL pipelines, data warehouses, and Azure data environments. Responsibilities include developing SSIS and Azure Data Factory solutions, creating Azure DevOps CI/CD pipelines, testing and debugging code, documenting procedures, improving data infrastructure, managing projects, and supporting SharePoint sites. The role requires collaboration with stakeholders, strong SQL and database design skills, and independent problem-solving.