Senior Data Analyst
BabbelNew York$100k – $110kPosted 27 March 2026
Tech Stack
Job Description
Senior Data Analyst
Enjoy working as an individual contributor and are passionate about learning languages? Join us! We are hiring a Senior Data Analyst to join our US team and provide actionable insights for our performance marketers.
About the Role:
Babbel is hiring a highly motivated and experienced Senior Data Analyst to join our data team, with a specific focus on supporting our Marketing and Revenue departments. In this role, you will play a crucial part in translating complex marketing and sales data into actionable insights that drive revenue growth and efficiency. You will work closely with marketing managers, product leads, and other stakeholders, providing data-driven recommendations and contributing to strategic initiatives. This role is ideal for a seasoned analyst looking to make a significant impact as an individual contributor on revenue generation and marketing effectiveness. This role will report directly into the Senior Analytics Manager.
Responsibilities:
- Marketing & Revenue Analysis: Conduct in-depth analysis of marketing campaign performance and sales data to identify opportunities for revenue growth and improved marketing ROI.
- Lead Generation and Conversion Analysis: Analyze lead generation activities and conversion funnels to identify bottlenecks and optimize lead nurturing strategies.
- Data Visualization and Reporting: Develop clear,concise dashboards and reports that effectively communicate marketing performance to stakeholders, including executive leadership.
- Business Partnering: Collaborate closely with marketing teams to understand business objectives, identify analytical needs, and provide data-driven solutions.
- Self-Serve Analytics Enablement: Build and maintain self-serve reporting frameworks so non-technical stakeholders can access data independently. This can be done either through our current BI structure or with the help of company owned AI tooling.
- Data Analysis and Interpretation: Conduct in-depth analysis of large datasets using various statistical methods and tools (e.g., SQL, Python/R, Excel, data visualization software). Identify trends, patterns, and anomalies to provide meaningful insights. Solve problems, uncover trends, and be the go-to for questions and issue resolution.
- Data Modeling and Database Management: Contribute to the development of data models, including our marketing attribution models, and databases. Have a strong understanding of database structures and query optimization.
- Data Quality and Integrity: Ensure data accuracy, consistency, and reliability by implementing data quality checks and validation processes. Identify and troubleshoot data quality issues.
- Data Governance: Contribute to documentation of data definitions, metrics dictionaries, and lineage — ensuring consistency across teams
- Mentorship and Knowledge Sharing: While this is an individual contributor role, you would recommend best practices within the larger data organization. Share knowledge and insights with the broader organization through presentations and documentation.
- Staying Current: Keep abreast of the latest trends and technologies in data analysis, business intelligence, and data science.
Qualifications:
- Bachelor's or Master's degree in a quantitative field (e.g., Statistics, Mathematics, Computer Science, Economics, Business, Data Analytics, Marketing)
- 3+ years of experience as a Data Analyst, with a proven track record of supporting marketing and/or revenue teams
- Strong proficiency in SQL/Python for data extraction and manipulation, experience with Databricks and dbt is a plus
- Experience with data visualization tools (e.g., Tableau) and Microsoft/Google suite of products (e.g., Excel and Spreadsheets). Experience with marketing analytics platforms, CRM systems is a plus
- Proficiency in at least one programming language for data analysis (e.g., Python, R)
- Solid understanding of marketing metrics and KPIs (e.g., CAC, LTV, ROAS)
- Experience ... (truncated, view full listing at source)
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