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About the role
Industry/Sector
Not Applicable
Specialism
Product Innovation
Management Level
Senior Associate
Job Description & Summary
The Opportunity Join our Acceleration Center India and help shape the future of business for our diverse client portfolio across geographies and jurisdictions. You’ll work at the heart of global teams across Advisory, Assurance, Tax and Business Services—solving real client challenges through connected collaboration. We’ll help you grow your skills so you can go further. With hands-on learning, cutting-edge tools and an inclusive culture, this is your opportunity to do inspiring work that makes a difference—every day. As a Software Engineer - AWS - Senior Associate you will contribute to data engineering solutions that support cloud-based modernization, including designing, building, and maintaining scalable services and data pipelines within our Cloud Engineering, Data & Analytics practice. As a Senior Associate you will analyze complex problems, manage assigned workstreams, guide junior team members, and use critical thinking to develop deliverables that align with client needs and broader project objectives. In this role at PwC Acceleration Center Bangalore, you will bring software engineering skills to data modernization efforts, collaborate across technical teams, and help develop solutions that support secure, reliable, and maintainable cloud environments. Responsibilities - Developing AWS-based data engineering solutions that support modern data platforms and client delivery workstreams - Building, testing, and maintaining data pipelines, data integrations, and transformation logic across cloud environments - Designing scalable data models and warehouse structures that support analytics, reporting, and downstream applications - Using Apache Airflow, Databricks, Snowflake, and AWS services to orchestrate and optimize data processing workflows - Troubleshooting performance, data quality, and query issues across databases, pipelines, and data warehouse layers - Applying data engineering methods to improve data architecture, validation, security, and access patterns - Translating business and technical requirements into deliverables that align with project scope and delivery timelines - Reviewing technical work from junior team members and providing guidance on engineering methods and code quality - Interpreting feedback from clients and project leads to refine solutions and address changing priorities - Contributing to discussions on cloud engineering, data modernization, and product innovation initiatives What You Must Have - At least a Bachelor's degree - At least 4 years of experience - Oral and written proficiency in English required
- Experience in architecting and delivering highly scalable, distributed, cloud-based enterprise data solutions
- Strong expertise in the end-to-end implementation of Cloud data engineering solutions like Enterprise Data Lake, Data hub in AWS
- Hands-on experience with Snowflake utilities, SnowSQL, SnowPipe,ETL data Pipelines, Big Data model techniques using
Python / Java
- Experience in loading disparate data sets and translating complex functional and technical requirements into detailed design
- Should be aware of deploying Snowflake features such as data sharing, events and lake-house patterns
- Should have experience with data security and data access controls and design
- Deep understanding of relational as well as NoSQL data stores, methods and approaches (star and snowflake, dimensional modeling)
- Proficient in Lambda and Kappa Architectures
- Strong AWS hands-on expertise with a programming background preferably Python/Scala
- Good knowledge of Big Data frameworks and related technologies - Experience in Hadoop and Spark is mandatory
- Strong experience in AWS compute services like AWS EMR, Glue and Sagemaker and storage services like S3, Redshift & Dynamodb
- Good experience with any one of the 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 What Sets You Apart - Preference for at least one of the following fields of study: Management Information Systems, Computer and Information Science, Systems Engineering, Electrical Engineering, Chemical Engineering, Industrial Engineering, Mathematics, Statistics, Mathematical Statistics - Demonstrating AWS data engineering workstreams across client engagements - Utilizing Apache Airflow, Databricks, or Snowflake in delivery - Translating data architecture needs into pipeline design choices - Applying analytical thinking to complex data modernization challenges - Mentoring junior team members through delivery tasks and feedback
Travel Requirements
Not Specified
Job Posting End Date
Skills required