Associate Manager

Job description

Job Summary We are looking for a skilled Google Cloud Data Engineer with 5-8 years of experience in designing, developing, and implementing scalable data engineering solutions on Google Cloud Platform (GCP). The ideal candidate should have strong expertise in building cloud-native ETL/ELT pipelines, BigQuery-based data warehouses, and large-scale data processing frameworks using PySpark, Dataflow, and Dataproc. Key Responsibilities • Design, develop, and deploy scalable ETL/ELT pipelines on Google Cloud Platform. • Architect and implement end-to-end data solutions leveraging GCP services and modern data engineering tools. • Build and optimize data processing applications using PySpark, Spark SQL, Dataflow, and Dataproc. • Develop robust data ingestion, transformation, and data quality frameworks for structured and unstructured data sources. • Implement and manage automated workflows using Apache Airflow or Cloud Composer. • Design and optimize data warehouse solutions using BigQuery. • Leverage GCP services including Cloud Storage, BigQuery, Dataproc, Dataflow, Cloud SQL, Bigtable, Datastore, and Spanner. • Monitor, troubleshoot, and improve the performance, reliability, and scalability of data pipelines. • Collaborate with business and technology teams to support data analytics and reporting requirements. • Ensure adherence to data governance, security, and best practices across cloud environments. Required Skills & Experience • 5- 8 years of experience in Data Engineering, Big Data, or Cloud Data Platform implementations. • Bachelors or Master’s degree in Computer Science, Engineering, or a related field. • Strong hands-on experience with Google Cloud Platform (GCP). • Expertise in BigQuery, SQL development, query optimization, and data warehousing concepts. • Strong proficiency in Python and SQL. • Hands-on experience with PySpark, Spark SQL, and distributed data processing frameworks. • Experience building data pipelines using Apache Beam, Google Dataflow, and Apache Spark. • Experience working with Dataproc, Cloud Storage, Cloud Composer, and Dataflow. • Knowledge of Hadoop ecosystem and data engineering best practices. • Experience working with relational, analytical, and NoSQL databases. • Ability to process and transform large-scale datasets efficiently. Preferred Qualifications • Google Cloud Professional Data Engineer Certification. • Google Cloud Professional Cloud Architect Certification. • Exposure to Machine Learning services on GCP is a plus. • Experience in cloud migration and modernization projects is an added advantage.