Senior Data Analyst (Full Stack)

As a Senior Data Analyst (Full Stack) at Blacklane, you will play a pivotal role in driving our data-led strategies, turning complex data into meaningful insights that shape business decisions. You will design and maintain dashboards, reports, and visualizations, partner with cross-functional teams to address their data needs, and perform advanced analyses. Your commitment to data quality and accuracy will be essential, as will your ability to clearly communicate findings and help steer the strategic direction of our data division within the engineering department. This role offers continuous learning, flexible work options, and the chance to thrive in a diverse, inclusive environment.

• Insights – Analyze complex datasets to identify trends, patterns, and actionable insights.
• Analysis – Perform advanced statistical analyses and predictive modeling to inform strategic decisions.
• Dashboards – Design, build, and maintain dashboards, reports, and data visualizations to monitor key metrics.
• Data Modeling – Take ownership of our data transformation layer, applying data modeling techniques (using dbt) to convert raw data into valuable analytical assets.
• Collaboration – Partner with cross-functional teams to understand business objectives and translate them into clear data requirements.
• Quality Mindset – Uphold data integrity and accuracy through thorough validation and rigorous quality checks.
• Business – Build deep expertise in specific business domains (such as Product, Marketing, Operations, or Sales) to serve as a trusted advisor to stakeholders.
• Communication – Clearly communicate findings and recommendations to stakeholders at all levels.

• Deep analytics experience: You have senior level experience (4+ years) in data analytics, with expert-level proficiency in SQL and dbt. Data modeling and creating insights are your passion.
• Proficiency in data visualization tools (e.g., Tableau, Metabase, Looker).
• Strong analytical and problem-solving skills with the ability to interpret complex datasets.
• Strong project management skills: highly organized, self-driven, and experienced in owning large-scale analytical projects.
• Excellent communication and presentation skills.