Sr. Data Analyst - Finance
New
United States, Multiple U.S. time zonesFull-TimeSenior
Salary$120,000 - $130,000
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Job Details
- Experience
- 3–5 years
- Required Skills
- SQLMicrosoft Power BISnowflakeTableauFinancial analysisData modelingBigQueryRedshiftLooker
Requirements
- 3–5 years of experience in data analytics, business intelligence, or financial analytics, ideally within a B2B SaaS or technology environment.
- Advanced SQL skills with experience writing optimized queries, using advanced functions, and managing large-scale data transformations.
- Experience designing and managing data models, pipelines, and reporting solutions.
- Hands-on experience with modern cloud data platforms and data warehousing technologies such as Snowflake, BigQuery, or Redshift.
- Strong experience with BI and visualization tools, with Tableau experience strongly preferred.
- Ability to support analytics engineering processes, from data ingestion through reporting and dashboard delivery.
- Strong analytical and problem-solving skills with the ability to independently investigate issues and deliver actionable insights.
- Experience improving processes through automation and scalable analytics solutions.
- Excellent communication skills with the ability to explain complex data concepts to business and technical audiences.
- Bachelor’s degree in Data Analytics, Finance, Economics, Statistics, Information Systems, or a related field preferred, or equivalent practical experience.
- Ability to work independently in a remote environment with strong ownership and accountability.
Responsibilities
- Design, build, and maintain scalable data models that support financial forecasting, budgeting, reporting, and ad-hoc analysis.
- Develop and optimize complex SQL queries for data extraction, transformation, and analysis across large datasets.
- Create, launch, and maintain automated executive-level dashboards and reporting solutions using BI tools such as Tableau, Power BI, or Looker.
- Partner with Data Engineering, Sales Operations, and Product teams to integrate and align data sources into a reliable finance data ecosystem.
- Support the development and maintenance of data pipelines, ensuring accuracy, completeness, consistency, and timely delivery of financial data.
- Establish and maintain strong data governance practices to ensure reliable information for leadership reporting, investor communications, and regulatory needs.
- Investigate complex data issues, identify root causes, and implement solutions to improve data quality and operational efficiency.
- Support automation initiatives and process improvements to increase scalability and enable self-service analytics.
- Translate complex financial and technical data findings into clear insights for both technical and non-technical stakeholders.
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