Senior Data Engineer

• Design, develop, and maintain scalable ETL/ELT pipelines using GCP-native services such as BigQuery, Cloud Composer (Airflow), Dataflow, Cloud Functions, and Cloud Storage
• Build optimized data ingestion frameworks for batch and streaming workloads
• Implement data transformation logic using SQL, Python, and Apache Beam
• Design and implement BigQuery partitioning, clustering, and optimization strategies for performance and cost efficiency
• Build reusable frameworks for ingestion, reconciliation, data quality, and metadata tracking
• Implement data validation, profiling, and monitoring to ensure data accuracy and completeness
• Establish best practices for error handling, logging, and alerting within pipelines
• Support data governance initiatives, including documentation, lineage, and change management
• Use CI/CD pipelines such as Cloud Build, GitLab CI/CD, and Jenkins to automate data-pipeline deployments
• Collaborate with Analytics, Product, Engineering, and business teams to gather requirements and design scalable data solutions

• 7+ years of experience in data engineering or related fields
• Strong expertise in Google Cloud Platform, including BigQuery, Cloud Composer/Airflow, Dataflow/Apache Beam, Pub/Sub, Cloud Storage, and Cloud Functions
• Strong SQL skills, including writing complex, optimized queries
• Hands-on experience using Python for data pipelines and automation
• Experience designing and executing ETL/ELT solutions in production
• Solid understanding of data warehousing concepts, dimensional modeling, and analytical data structures
• Experience with Git-based version control and CI/CD pipelines
• Domain experience in the Fintech industry (nice to have)
• Experience using AWS data services such as S3 and Glue (nice to have)
• Strong problem-solving skills and ability to troubleshoot complex data issues
• Excellent communication and documentation skills
• Ability to work independently and manage priorities in a fast-paced environment
• Collaborative mindset with ability to work cross-functionally