Skills required: Must have experience with: Designing and building scalable data pipelines and ETL workflows to support analytical data warehouses; Developing complex SQL queries, views, stored procedures, and user-defined functions in cloud databases including Google BigQuery; Optimizing long-running queries and improving performance of large-scale analytical datasets; Parsing, cleansing, and transforming structured and unstructured data using Hive, Spark, and PySpark; Developing automation scripts and reusable tools using Python; Designing and implementing data models to support reporting, dashboarding, and self-service BI; Working with cloud platforms, including Google Cloud Platform (preferred), AWS, Azure, and Snowflake at scale; Leveraging cloud data pipeline orchestration tools: Airflow, Dataflow; Building analytical datasets to support Tableau and Looker; Performing data exploration and statistical analysis to uncover business insights and common data pitfalls; Identifying data bottlenecks and implementing optimization strategies to enhance pipeline efficiency and data reliability; Producing technical documentation including data architecture diagrams, source-to-target mappings, and ETL workflow designs. Minimum education and experience required: Master's degree or the equivalent in Computer Science, Information Technology, Engineering (any), Statistical Science, or a related field plus 1 year of experience in software engineering or related experience; OR Bachelor's degree or the equivalent in Computer Science, Information Technology, Engineering (any), Statistical Science, or a related field plus 3 years of experience in software engineering or related experience.