IN_Senior Associate_AWS_PySpark_AI_ML_D&A_Advisory_PAN India

Job Description & Summary: PwC India is seeking a highly skilled AWS, PySpark, and AI/ML Developer with hands-on experience in designing, developing, and deploying scalable data pipelines and machine learning models on cloud platforms. This role focuses on leveraging AWS services, big data processing frameworks like PySpark, and AI/ML techniques to build advanced analytics solutions that drive business value across diverse domains. Job Position Title: IN_Senior Associate_AWS_PySpark_AI_ML_D&A_Advisory_PAN India Responsibilities: Design, develop, and deploy end-to-end data processing pipelines using PySpark on AWS EMR or equivalent platforms. Build, train, and optimize machine learning models using AWS SageMaker or other AI/ML frameworks to solve complex business problems. Develop scalable, reliable, and reusable ETL workflows integrating various AWS data services such as S3, Lambda, Glue, Redshift, and Kinesis. Collaborate with data scientists, analysts, and architects to translate business requirements into technical AI/ML solutions. Implement data ingestion, transformation, and quality validation processes ensuring data integrity and consistency. Tune PySpark jobs for optimal performance and cost-efficiency in a distributed computing environment. Monitor, troubleshoot, and optimize cloud infrastructure and data pipeline performance. Apply ML lifecycle management including model versioning, deployment, monitoring, and retraining. Produce technical documentation including solution designs, code documentation, and operational runbooks. Stay updated on emerging AWS services, big data technologies, and machine learning advancements to recommend best practices and improvements. Mandatory skill sets: Strong hands-on experience with AWS cloud technologies including AWS EMR, S3, Glue, Lambda, SageMaker, Redshift, and related services. Proficiency in developing big data processing pipelines using PySpark and Apache Spark ecosystem. Experience building and deploying AI/ML models using AWS SageMaker or other ML frameworks (e.g. TensorFlow, Scikit-learn, PyTorch). Expertise in data engineering principles, ETL design, and distributed data processing at scale. Solid programming skills in Python and familiarity with Spark SQL and data frame APIs. Ability to design and implement robust, scalable, and secure cloud-native solutions. Understanding of ML lifecycle, including feature engineering, model training, evaluation, and deployment. Knowledge of cloud security best practices, IAM roles and policies on AWS. Excellent problem-solving, analytical, and communication skills. Preferred skill sets: Experience with containerization and orchestration technologies like Docker and Kubernetes. Familiarity with infrastructure as code tools such as CloudFormation or Terraform. Experience with data visualization and business intelligence tools. Prior consulting experience delivering cloud-based data and AI/ML solutions for enterprise clients. Exposure to real-time streaming and event-driven architectures using AWS Kinesis or Kafka. Years of experience required: 4 - 7 Years Education qualification: BE, <B.Tech>, MCA, MBA, <M.Tech>