StackAdapt is the leading technology company that empowers marketers to reach, engage, and convert audiences with precision. With 465 billion automated optimizations per second, the AI-powered StackAdapt Marketing Platform seamlessly connects brand and performance marketing to drive measurable results across the entire customer journey. The most forward-thinking marketers choose StackAdapt to orchestrate high-impact campaigns across programmatic advertising and marketing channels.

We're looking for an Analyst to join our Data Architecture team. This role sits within our Analytics and Reporting Insights team under the greater Revenue organization. In this role, you will manage data requests, improve data pipelines, and deliver solutions that enhance both internal efficiency and client outcomes. This role blends technical hands-on work with business collaboration.

You’ll partner with analytics, product, engineering and business stakeholders to design pipelines, optimize data models, and set up the foundation for scalable insights.

What You'll Be Doing:

• Manage standard data and reporting requests from internal teams with accuracy and speed.
• Build and optimize data pipelines and transformations using SQL and Python and orchestration tools like Kestra.
• Collaborate with analytics and business teams to understand data requirements and translate them into scalable solutions.
• Ensure data quality, governance, and consistency across reporting and analytics environments.
• Contribute to the team’s AI initiatives by preparing structured datasets for modeling and experimentation.
• Support visualization and reporting efforts in Tableau/ThoughtSpot, enabling self-serve access to business teams.
• Proactively identify opportunities to improve data efficiency, reliability, and usability.
• Establish and document data architecture standards and best practices for reusability and consistency.
• Support peer learning through documentation, code reviews, and sharing of best practices within the data team.

What You'll Bring to the Table

• 2-3+years experience in Business Intelligence Engineering, Data Engineering, Data Analysis or Data Science roles in a fast moving, high impact software or technology environment.
• Previous experience building data pipelines and analyzing large datasets to solve problems
• Advanced SQL skills including complex joins and window functions with experience in large-scale data warehousing (Snowflake, Redshift, or BigQuery).
• Proficiency in Python for data processing and automation.
• Hands-on experience with workflow orchestration (Airflow or equivalent).
• Understanding of data modeling best practices and query optimization.
• Strong problem-solving skills with attention to detail and data accuracy.
• Comfortable collaborating across functions to identify data analytics problems and execute solutions with technical rigor and data-driven insights.
• Familiarity with modern ML and AI data workflows, from feature engineering to preparing structured and unstructured data for downstream models, including emerging use cases involving LLMs or vector databases.
• Exposure to BI tools like Tableau (or similar) is a strong asset
• Strong understanding of data in digital marketing and programmatic environments, including campaign, audience, and attribution data models is a strong asset