Senior Data Analyst

Posted 4 months agoViewed

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💎 Seniority level: Senior, 5+ years

📍 Location: Europe, APAC, Americas

🔍 Industry: Technology, software development

⏳ Experience: 5+ years

🪄 Skills: LeadershipSQLBusiness IntelligenceData AnalysisETLSnowflakeStrategyCommunication SkillsCollaboration

Requirements:

5+ years of experience in data analysis, business intelligence, or a related field, with a proven ability to deliver impactful data solutions in fast-paced environments.
Advanced proficiency in SQL and strong experience with data warehousing and ETL/ELT processes.
Familiarity with Snowflake, DBT, and Looker is highly desirable.
Strong analytical thinking with the ability to interpret data, identify trends, and generate actionable insights to inform business decisions.
Exceptional communication skills, with the ability to distill complex technical concepts for both technical and non-technical audiences.
Experience mentoring junior team members and contributing to team development.
Ability to influence and lead cross-functional teams in data-driven initiatives.
Bachelor’s or Master’s degree in a relevant field such as Data Science, Computer Science, Statistics, Economics, or Mathematics.
A meticulous approach to data, ensuring accuracy and reliability in all deliverables, while maintaining a high standard of data quality.

Responsibilities:

Lead data initiatives by designing, developing, and optimizing data models and reporting structures that support the organization’s strategic objectives.
Conduct advanced data analysis, leveraging tools like Snowflake, DBT, and SQL to ensure accuracy, consistency, and actionable insights across various data sources.
Develop and maintain scalable, robust data models that enable both real-time and ad-hoc analysis, driving key business decisions.
Create, manage, and optimize dashboards and reports using Looker, providing stakeholders with clear, actionable insights.
Partner closely with business teams, data engineers, and leadership to understand and meet data needs, aligning data initiatives with broader business goals.
Provide mentorship to other analysts, fostering professional growth and encouraging best practices across the team.
Drive data quality initiatives, identifying and resolving inconsistencies while defining best practices for data governance.
Continuously refine and enhance data models, reporting pipelines, and processes to support evolving business needs and ensure scalability.

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