DT - Senior Software Engineer

Overview We are looking for a skilled and detail-oriented GCP Data Engineer to join our growing data engineering team. The ideal candidate will have hands-on experience designing, building, and optimizing scalable data pipelines on Google Cloud Platform, along with strong problem-solving and communication skills to collaborate effectively with cross-functional and global stakeholders. Responsibilities Key Responsibilities Design, develop, and maintain robust, scalable, and efficient data pipelines on Google Cloud Platform (GCP). Work extensively with BigQuery (BQ) for data warehousing, query optimization, and large-scale data analysis. Build and manage big data processing workflows using Dataproc (Hadoop/Spark ecosystem on GCP). Write, optimize, and troubleshoot complex SQL queries for data transformation, validation, and reporting. Design, schedule, and monitor data workflows using Cloud Composer (Apache Airflow). Perform root-cause analysis and troubleshooting of pipeline failures, data quality issues, and performance bottlenecks in production environments. Collaborate with data analysts, data scientists, and business stakeholders to understand requirements and deliver reliable data solutions. Ensure data governance, security, and compliance standards are followed across all GCP data engineering solutions. Participate in code reviews, design discussions, and knowledge-sharing sessions within the team. Document technical designs, data flows, and operational runbooks for supportability. Requirements Required Technical Skills Skill Proficiency Expected Google Cloud Platform (GCP) Strong hands-on experience BigQuery (BQ) Query optimization, partitioning, clustering, cost management Dataproc Spark/Hadoop job design and management SQL Advanced query writing, performance tuning Cloud Composer / Apache Airflow DAG design, scheduling, monitoring Troubleshooting Strong analytical and debugging skills for pipeline/data issues Good to Have (Additional Skills) Ab Initio – ETL development and pipeline migration experience. DevOps – CI/CD pipelines, version control (Git), containerization (Docker/Kubernetes), infrastructure as code (Terraform) is a plus. Prior Data/ETL Migration Experience – Hands-on experience migrating data pipelines, ETL workloads, or on-premise data warehouses to cloud platforms (e.g., on-prem to GCP, or cross-cloud migrations) is a strong value add. Soft Skills Excellent communication skills – ability to clearly articulate technical concepts to both technical and non-technical stakeholders. Strong ownership mindset and ability to work independently as well as within a team. Good stakeholder management skills, especially in a global/MNC delivery environment. Ability to work under pressure and manage multiple priorities in a fast-paced environment. Qualifications Bachelor's/Master's degree in Computer Science, Information Technology, Engineering, or a related field. GCP certification (e.g., Professional Data Engineer) is a plus.

Key Responsibilities Design, develop, and maintain robust, scalable, and efficient data pipelines on Google Cloud Platform (GCP). Work extensively with BigQuery (BQ) for data warehousing, query optimization, and large-scale data analysis. Build and manage big data processing workflows using Dataproc (Hadoop/Spark ecosystem on GCP). Write, optimize, and troubleshoot complex SQL queries for data transformation, validation, and reporting. Design, schedule, and monitor data workflows using Cloud Composer (Apache Airflow). Perform root-cause analysis and troubleshooting of pipeline failures, data quality issues, and performance bottlenecks in production environments. Collaborate with data analysts, data scientists, and business stakeholders to understand requirements and deliver reliable data solutions. Ensure data governance, security, and compliance standards are followed across all GCP data engineering solutions. Participate in code reviews, design discussions, and knowledge-sharing sessions within the team. Document technical designs, data flows, and operational runbooks for supportability.

Required Technical Skills Skill Proficiency Expected Google Cloud Platform (GCP) Strong hands-on experience BigQuery (BQ) Query optimization, partitioning, clustering, cost management Dataproc Spark/Hadoop job design and management SQL Advanced query writing, performance tuning Cloud Composer / Apache Airflow DAG design, scheduling, monitoring Troubleshooting Strong analytical and debugging skills for pipeline/data issues Good to Have (Additional Skills) Ab Initio – ETL development and pipeline migration experience. DevOps – CI/CD pipelines, version control (Git), containerization (Docker/Kubernetes), infrastructure as code (Terraform) is a plus. Prior Data/ETL Migration Experience – Hands-on experience migrating data pipelines, ETL workloads, or on-premise data warehouses to cloud platforms (e.g., on-prem to GCP, or cross-cloud migrations) is a strong value add. Soft Skills Excellent communication skills – ability to clearly articulate technical concepts to both technical and non-technical stakeholders. Strong ownership mindset and ability to work independently as well as within a team. Good stakeholder management skills, especially in a global/MNC delivery environment. Ability to work under pressure and manage multiple priorities in a fast-paced environment. Qualifications Bachelor's/Master's degree in Computer Science, Information Technology, Engineering, or a related field. GCP certification (e.g., Professional Data Engineer) is a plus.