IN Senior Associate AWS DataOps Engineer

Job Description

Not Applicable Specialism SAP Management Level Senior Associate & Summary At PwC, our people in data and analytics engineering focus on leveraging advanced technologies and techniques to design and develop robust data solutions for clients. They play a crucial role in transforming raw data into actionable insights, enabling informed decisionmaking and driving business growth. In data engineering at PwC, you will focus on designing and building data infrastructure and systems to enable efficient data processing and analysis. You will be responsible for developing and implementing data pipelines, data integration, and data transformation solutions. Why PWC At PwC, you will be part of a vibrant community of solvers that leads with trust and creates distinctive outcomes for our clients and communities. This purposeled and valuesdriven work, powered by technology in an environment that drives innovation, will enable you to make a tangible impact in the real world. We reward your contributions, support your wellbeing, and offer inclusive benefits, flexibility programmes and mentorship that will help you thrive in work and life. Together, we grow, learn, care, collaborate, and create a future of infinite experiences for each other. Learn more about us . & Summary We are looking for a seasoned AWS DataOps Engineer Responsibilities Design, implement, and manage scalable data pipelines and ETL processes on AWS. Collaborate with data teams to understand requirements and translate them into robust data solutions. Proven experience with AWS data services such as S3, Redshift, RDS, Glue, and Lambda. Strong understanding of data architecture, data modeling, and data warehousing concepts. Strong programming and scripting skills in languages like Python, SQL, or Shell scripting. Experience with data pipeline and ETL tools, such as Apache Airflow or AWS Data Pipeline. Ensure data quality, integrity, and security through automated testing, monitoring, and alerting systems. Optimize data storage and retrieval using AWS services such as S3, Redshift, RDS, and DynamoDB. Implement data governance and compliance standards to ensure data privacy and security. Automate data integration and deployment processes using tools like AWS Data Pipeline, Glue, and Step Functions. Monitor and troubleshoot data workflows to ensure reliability and performance. Provide technical support and guidance to data teams on best practices for data management and operations. Mandatory skill sets (AWS, Azure, GCP) services such as GCP BigQuery, Dataform AWS Redshift, Python Preferred skill sets Devops Years of experience required 48 Years Education qualification BE/B.Tech/MBA/MCA/M.Tech Education Degrees/Field of Study required Master of Business Administration, Master of Engineering, Bachelor of Engineering Degrees/Field of Study preferred Required Skills DevOps Accepting Feedback, Accepting Feedback, Active Listening, Agile Scalability, Amazon Web Services (AWS), Analytical Thinking, Apache Airflow, Apache Hadoop, Azure Data Factory, Communication, Creativity, Data Anonymization, Data Architecture, Database Administration, Database Management System (DBMS), Database Optimization, Database Security Best Practices, Databricks Unified Data Analytics Platform, Data Engineering, Data Engineering Platforms, Data Infrastructure, Data Integration, Data Lake, Data Modeling, Data Pipeline {+ 27 more} Travel Requirements Government Clearance Required?