Data Engineer - Python

Description : We are seeking a skilled Data Engineer to design, build, and maintain data pipelines and data models that support analytical and business intelligence needs. The ideal candidate will have hands-on experience with Python or SQL, Google Cloud Platform (GCP), and a strong understanding of data management, quality, and security best practices. Key Responsibilities : - Build and maintain moderately complex data pipelines, ensuring data flow, transformation, and usability for analytical projects. - Design and implement data models, optimizing for performance and scalability. - Apply knowledge of data characteristics and supply patterns to develop rules and tracking processes that support data quality models. - Prepare data for analytical use by gathering, integrating, cleansing, and structuring data from multiple sources and systems. - Perform design, creation, and interpretation of large and highly complex datasets. - Troubleshoot pipeline and data issues to ensure accuracy and reliability. - Stay up-to-date with GCP advancements and recommend innovative solutions. - Implement security best practices within data pipelines and cloud infrastructure. - Collaborate with global teams to share and adopt best practices in data management, maintenance, reporting, and security. - Develop and execute data quality checks to ensure consistency and integrity. - Work with credit data products and perform analysis using tools like Google BigQuery, BigTable, DataFlow, and Spark/PySpark. Mandatory Skills : - Python or SQL Proficiency : Experience with Python or SQL and intermediate scripting for data manipulation and processing. - GCP & Cloud Fundamentals : Intermediate understanding and experience with Google Cloud Platform (GCP) and overall cloud computing concepts. - Data Pipeline Construction : Proven ability to build, maintain, and troubleshoot moderately complex pipelines. - Data Modeling & Optimization : Experience designing and optimizing data models for performance. - Data Quality Governance : Ability to develop rules, tracking processes, and checks to support a data quality model. - Data Preparation & Structuring : Skilled in integrating, consolidating, cleansing, and structuring data for analytical use. - Security Implementation : Knowledge of security best practices in pipelines and cloud infrastructure. - Big Data Analysis Tools : Hands-on experience with Google BigQuery, BigTable, DataFlow, Scala + Spark or PySpark. - Advanced Data Formats : Experience working with JSON, AVRO, and PARQUET formats. - Communication & Best Practices : Strong communication skills to promote global best practices and guide adoption. Preferred Qualifications : - Cloud certification (e.g., GCP Data Engineer, AWS, Azure). - Experience with credit data products. - Familiarity with data governance frameworks and metadata management tools.