Job
Description
Role Overview: You will be responsible for architecting and delivering highly scalable, distributed, cloud-based enterprise data solutions. Your role will involve designing scalable data architectures with Snowflake, integrating cloud technologies such as AWS, Azure, GCP, and ETL/ELT tools like DBT. Additionally, you will guide teams in proper data modeling, transformation, security, and performance optimization. Key Responsibilities: - Architect and deliver highly scalable, distributed, cloud-based enterprise data solutions - Design scalable data architectures with Snowflake and integrate cloud technologies like AWS, Azure, GCP, and ETL/ELT tools such as DBT - Guide teams in proper data modeling (star, snowflake schemas), transformation, security, and performance optimization - Load data from disparate data sets and translate complex functional and technical requirements into detailed design - Deploy Snowflake features such as data sharing, events, and lake-house patterns - Implement data security and data access controls and design - Understand relational and NoSQL data stores, methods, and approaches (star and snowflake, dimensional modeling) - Utilize AWS, Azure, or GCP data storage and management technologies such as S3, Blob/ADLS, and Google Cloud Storage - Implement Lambda and Kappa Architectures - Utilize Big Data frameworks and related technologies, with mandatory experience in Hadoop and Spark - Utilize AWS compute services like AWS EMR, Glue, and Sagemaker, as well as storage services like S3, Redshift, and DynamoDB - Experience with AWS Streaming Services like AWS Kinesis, AWS SQS, and AWS MSK - Troubleshoot and perform performance tuning in Spark framework - Spark core, SQL, and Spark Streaming - Experience with flow tools like Airflow, Nifi, or Luigi - Knowledge of Application DevOps tools (Git, CI/CD Frameworks) - Experience in Jenkins or Gitlab with rich experience in source code management like Code Pipeline, Code Build, and Code Commit - Experience with AWS CloudWatch, AWS Cloud Trail, AWS Account Config, AWS Config Rules Qualifications Required: - 8-12 years of relevant experience - Hands-on experience with Snowflake utilities, SnowSQL, SnowPipe, ETL data Pipelines, Big Data model techniques using Python/Java - Strong expertise in the end-to-end implementation of Cloud data engineering solutions like Enterprise Data Lake, Data hub in AWS - Proficiency in AWS, Data bricks, and Snowflake data warehousing, including SQL, Snow pipe - Experience in data security, data access controls, and design - Strong AWS hands-on expertise with a programming background preferably Python/Scala - Good knowledge of Big Data frameworks and related technologies, with mandatory experience in Hadoop and Spark - Good experience with AWS compute services like AWS EMR, Glue, and Sagemaker and storage services like S3, Redshift & Dynamodb - Experience with AWS Streaming Services like AWS Kinesis, AWS SQS, and AWS MSK - Troubleshooting and Performance tuning experience in Spark framework - Spark core, SQL, and Spark Streaming - Experience in one of the flow tools like Airflow, Nifi, or Luigi - Good knowledge of Application DevOps tools (Git, CI/CD Frameworks) - Experience in Jenkins or Gitlab with rich experience in source code management like Code Pipeline, Code Build, and Code Commit - Experience with AWS CloudWatch, AWS Cloud Trail, AWS Account Config, AWS Config Rules Kindly share your profiles on dhamma.b.bhawsagar@pwc.com if you are interested in this opportunity.,
