Junior Data Analyst

• We are seeking a technically strong Junior Data Analyst to support Marketing Analytics by transforming data into insights that improve campaign performance and enable data & AI driven decision-making
• This is an early-career role ideal for candidates with strong analytical fundamentals and hands-on experience with SQL, Python, Claude Code, and modern data platforms such as Databricks
• You will work with large marketing datasets, develop reporting solutions, automate data workflows, implement AI agentic layers and partner with marketing business partners to deliver actionable insights
• 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
• Hands-on experience working with large-scale marketing and customer datasets
• Mentorship & development in SQL, Python, Databricks and modern analytics tools
• Opportunities to influence marketing strategy through data insights
• Exposure to cloud-based analytics and data engineering practices
• A strong career development foundation in data analytics and marketing analytics

Benefits

• Paid parental leave: 8 weeks for all parents, 16 weeks for birthing parents
• Unlimited paid time off, plus 3 global VeeaMe Days for self-care
• Medical, dental, and vision coverage from day one
• Mental health support, therapy sessions, and digital wellness tools via SupportLinc EAP
• 401(k) retirement plan with matching contributions up to annual limits
• Fertility, adoption, and surrogacy support through Maven, plus paid volunteer time
• AirVet: 24/7 virtual veterinary care at no cost
• Legal services, identity protection, and supplemental health insurance options
• Professional training and education, including courses and workshops, internal meetups, and unlimited access to our online learning platforms (LinkedIn Learning, Athena, O’Reilly) and mentoring through our MentorLab program
• Tax-advantaged spending accounts for healthcare, dependent care, and commuting- Strong working knowledge of SQL, including joins, aggregations, and data transformations
• Internship, academic project, or research experience involving data analysis is strongly preferred
• Basic to intermediate proficiency in Python with experience using data libraries (e.g., pandas, NumPy) through coursework, projects, or internships
• Strong curiosity and willingness to learn
• Strong analytical and problem-solving abilities with attention to detail
• Bachelor’s degree in Data Analytics, Computer Science, Statistics, Business Analytics, Marketing Analytics, or related quantitative field
• Ability to manage multiple workflow priorities using Jira or similar project management tools and work independently
• Experience working with real-world datasets and performing data validation and troubleshooting
• Ability to communicate technical findings to non-technical audiences
• Exposure to Databricks, Apache Spark, or cloud-based data environments
• Experience with Tableau, Power BI, or similar visualization tools
• Familiarity with marketing analytics concepts or campaign performance metrics
• Exposure to marketing platforms such as Google Analytics or Salesforce
• Experience using version control tools (e.g., Git)
• Understanding of ETL or data pipeline concepts