Senior Analytics Engineer

🕒 August 6

🇺🇸 United States – Remote

⏰ Full Time

🟠 Senior

📊 Analytics Engineer

👻 Ghost score 12%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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EXL

WebsiteLinkedInAll Job Openings

10,000+ employees

🏥 Healthcare

🛡️ Insurance

📦 Logistics

💰 $2M Venture Round on 2015-01

Healthcare • Insurance • Logistics

EXL is a business consulting and services firm that focuses on leveraging data to enhance business operations and decision-making. With a strong emphasis on collaboration and adaptability, EXL partners with organizations to address their unique needs and culture while integrating data science and technology solutions. The company's areas of expertise include operations management, decision analytics, digital transformation, and various industries such as healthcare, finance, and insurance. EXL's mission is to help clients drive business evolution and maintain competitive advantage through tailored solutions and effective use of data.

📋 Description

• Design, build, and maintain scalable analytics engineering solutions using Databricks, Unity Catalog, and modern data platforms • Develop and manage metrics-as-code frameworks for standardized, governed, reusable business metrics • Implement metric, cohort, segment, and KPI definitions in semantic layers and measurement platforms • Build and optimize Workstream Scorecards connecting objectives, business drivers, performance indicators, and actionable insights • Develop automated data pipelines for metric refreshes, data validation, and reporting workflows • Create reusable analytics assets, frameworks, and data products to accelerate adoption and decision-making • Establish practices for data modeling, metric governance, version control, testing, and deployment • Partner with Data Engineering on source data requirements, event tracking standards, and instrumentation strategies • Improve data quality, observability, lineage, and governance across analytics environments • Translate business questions into measurable product KPIs and actionable insights with client stakeholders • Develop product measurement frameworks for engagement, retention, acquisition, conversion, and customer lifecycle performance • Support experimentation through metric definition, experiment design consultation, and outcome measurement • Build and maintain customer cohorts, segmentation frameworks, and behavioral analysis models • Champion CI/CD, code reviews, testing, and release management in analytics development • Manage Git-based development workflows and deployment pipelines • Document metric definitions, business logic, transformation rules, and data quality considerations

🎯 Requirements

• Bachelor's Degree • 4+ years of experience in Analytics Engineering, Product Analytics, Data Analytics, or Business Intelligence • Advanced SQL expertise analyzing large-scale event, clickstream, behavioral, or customer interaction data • Hands-on experience with Databricks, Unity Catalog, Delta Lake, and modern cloud data platforms • Experience with metrics-as-code and semantic layer technologies such as dbt, Cube, MetricFlow, or similar frameworks • Proficiency in Python for analytics, data processing, automation, and testing • Experience with Git, CI/CD pipelines, code repositories, and software development lifecycle practices • Understanding of product analytics concepts including funnels, cohorts, DAU/WAU/MAU, retention, engagement, conversion, and customer journey analysis • Experience partnering with product, engineering, and business stakeholders to deliver analytical solutions • Experience working in agile delivery environments and distributed teams