
Data Analyst
4 weeks ago
Overview
We are seeking a detail-oriented and technically skilledData Analyst who can bridge data engineering and analytics to deliver meaningful insights for clients. The ideal candidate will have strong experience in building and managing data pipelines, working with CRMs, and creating dashboards, while also being confident in engaging with clients to understand requirements and present solutions clearly.
Core Technical SkillsSQL and Python (critical).
Strong experience withETL tools (Fivetran, Matillion) anddata warehouses (AWS Redshift).
Experience inTableau andPower BI for data visualization.
Familiarity withGA4, Adobe Analytics, CRO, tag managers, and CDPs .
Proficiency withSalesforce ; exposure to Oracle NetSuite and Oracle Business Suite is a plus.
Basic knowledge of Java, HTML, CSS, and JavaScript.
Exposure to or experience withUS healthcare industry data is a strong advantage.
Understanding ofdata privacy regulations (HIPAA, GDPR) and cookie consent practices.
Client-facing communication : Comfortable presenting insights and engaging directly with stakeholders.
Problem-solving : Ability to manage complex, siloed datasets and propose effective solutions.
Adaptability : Eager and able to learn new tools, technologies, and datasets quickly.
Collaboration : Works well in cross-functional teams and can adapt to varying client MarTech stacks.
Build and manageETL pipelines (e.g., Fivetran, Matillion) and integrate data from multiple sources (Salesforce, Oracle NetSuite, Oracle Business Suite).
Maintain and optimizedata warehouses (AWS Redshift or similar).
Performdata analysis and reporting using SQL, Python, Tableau, and Power BI.
Define and implementmeasurement models, KPIs, and metrics to support business decision-making.
Supportwebsite and marketing analytics (GA4, Adobe Analytics, tag managers, CRO), with flexibility to learn new tools as needed.
Ensure compliance withdata privacy standards (HIPAA, GDPR, cookie consent tools like OneTrust).
Collaborate with stakeholders to gather requirements, translate business needs into data solutions, and present insights effectively.
Troubleshoot siloed datasets and recommend solutions for centralization and better decision-making.
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