Lead Data Engineer - PySpark

About the Role: Join our data engineering team to build and maintain large-scale data pipelines that power analytics across various products. In this role, you will process a large amount of data to deliver actionable insights for product teams and executives. What You'll Do: ● Develop Apache Airflow DAGs and PySpark ETL pipelines for high volume data processing. ● Write optimized SQL queries for data transformation and aggregation. ● Build data products serving Business Process, Executive KPIs, and Product Analytics. ● Implement data quality and monitoring solutions. ● Optimize pipeline performance and troubleshoot production issues. ● Collaborate with cross-functional teams. ● Production Pipeline Monitoring (KLO). Qualifications: Required Skills ● 10+ years of data engineering experience with a minimum of 7 years dedicated to the Big data stack. ● Expert in Python and PySpark (DataFrame API, Spark SQL). ● Advanced SQL skills (window functions, complex queries). ● Production experience with Apache Airflow. ● Solid background in data warehousing and dimensional modelling. Preferred Skills ● Experience with SQL, Trino, Apache Iceberg. ● Knowledge of Tableau CRM/CLOUD, Salesforce platforms. ● AWS/cloud data services experience.