Analyze marketing performance data to identify trends, optimization opportunities, and key performance drivers.
Evaluate customer acquisition, engagement, and conversion metrics to support marketing strategy.
Design and implement an intelligent lead ingestion framework by automating the lead import process using AI-driven data parsing, validation, and enrichment techniques. This includes building scalable process automation pipelines and developing a user-friendly interface that enables seamless monitoring, control, and interaction with incoming lead data.
Translate complex data into clear insights and recommendations for stakeholders.
Support ad-hoc analysis and proactively identify opportunities for deeper insights.
Write efficient SQL queries to extract, transform, and analyze marketing and enterprise data.
Use Python for data cleaning, automation, and exploratory analysis.
Assist with building and maintaining curated datasets, data models, and data quality checks
Use Claude Code to design interfaces, agents & automation steps
Develop and maintain dashboards and marketing performance reports using BI tools.
Automate recurring reporting processes to improve efficiency and scalability.
Partner with marketing, analytics, data science and data engineering teams to support reporting and data needs.
Document data definitions, logic, and reporting methodologies.

Strong working knowledge of SQL, including joins, aggregations, and data transformations.
Basic to intermediate proficiency in Python with experience using data libraries (e.g., pandas, NumPy) through coursework, projects, or internships.
Exposure to Databricks, Apache Spark, or cloud-based data environments.
Experience working with real-world datasets and performing data validation and troubleshooting.
Strong curiosity and willingness to learn.
Strong analytical and problem-solving abilities with attention to detail.
Ability to communicate technical findings to non-technical audiences.
Ability to manage multiple workflow priorities using Jira or similar project management tools and work independently.
Bachelor’s degree in Data Analytics, Computer Science, Statistics, Business Analytics, Marketing Analytics, or related quantitative field.
Internship, academic project, or research experience involving data analysis is strongly preferred.

25 paid vacation days, plus 4 extra global VeeaMe Days for self-care and 24 paid volunteer hours annually through Veeam Cares
Private medical, dental, and vision insurance with dependent enrolment
Life insurance with enhanced coverage and global 24/7 protection
Income protection after 26 weeks, covering a portion of salary
Defined contribution pension plan with employer match
Worldwide travel insurance for business and leisure, with option to enroll dependents
Employee Assistance Program with therapy, legal, and financial support, plus online GP services and wellbeing programs
Opportunities to learn and grow through on-demand libraries (LinkedIn Learning, O’Reilly), mentoring, workshops and learning events like our annual Global Day of Learning

Junior Data Analyst

Key skills