Job Title : Data Engineer (Analyst)
Experience : 2+ Years
Location : Remote
About the Role :
We are looking for an experienced Data Engineer (Analyst) who can design, build, and optimize data models and pipelines to support business intelligence and performance analytics. The ideal candidate should have a strong understanding of SQL, cloud data warehouses (preferably Snowflake), and hands-on experience with advertising or marketing data.
Key Responsibilities :
- Design, build, and maintain scalable data pipelines and analytical models for advertising events such as impressions, clicks, and conversions.
- Analyze programmatic advertising data across multiple platforms (DSPs, ad exchanges, social networks).
- Support campaign performance analysis and provide data-driven insights to optimize marketing effectiveness.
- Conduct A / B testing and experimental analysis to evaluate campaign performance and creative strategies.
- Track and interpret user behavior data using tools like Heap, Google Analytics, or similar platforms.
- Develop and optimize SQL queries and manage ETL / ELT workflows in Snowflake or similar cloud data environments.
- Collaborate with business stakeholders, product managers, and data teams to define key metrics, KPIs, and reporting requirements .
- Build interactive dashboards and reports using BI tools such as Power BI, Tableau, Looker, or Sigma.
- Ensure data quality, consistency, and governance across analytics datasets.
Required Skills :
Strong proficiency in SQL (joins, CTEs, window functions, aggregations, and query optimization).Hands-on experience with Snowflake or other cloud data warehouses .Solid understanding of programmatic advertising data (impressions, clicks, CTR, CPM, conversions, ROAS, etc.).Experience with A / B testing frameworks and conversion rate analysis .Familiarity with Heap , Google Analytics , or similar behavioral analytics tools .Practical experience with BI tools such as Power BI, Tableau, Looker, or Sigma.Strong analytical, problem-solving, and data storytelling skills .Knowledge of ETL / ELT processes , data governance , and data quality management .