NTT Data - AWS Data Engineer

: We are looking for an experienced AWS Data Engineer to join our data engineering team and play a key role in designing, developing, and maintaining scalable data solutions on the AWS cloud platform. The ideal candidate should have strong hands-on experience in data engineering, AWS services, ETL/ELT pipelines, data warehousing, and big data technologies. You will work closely with data architects, data scientists, analysts, product teams, and business stakeholders to build reliable and high-performing data platforms that support analytics, reporting, and data-driven decision-making. Key Responsibilities : - Design, develop, and maintain scalable and reliable data pipelines using AWS cloud services. - Build and optimize ETL/ELT workflows for processing structured and unstructured data from multiple sources. - Develop data ingestion, transformation, and integration solutions using appropriate AWS services. - Work with services such as Amazon S3, AWS Glue, Amazon Redshift, Amazon EMR, Lambda, Kinesis, Athena, Step Functions, and CloudWatch. - Design and implement data models, data warehouses, and data lakes to support business and analytical requirements. - Develop efficient and reusable data transformation frameworks using Python, SQL, PySpark, or similar technologies. - Ensure data quality, accuracy, consistency, security, and governance across data pipelines. - Monitor pipeline performance, troubleshoot failures, and optimize data processing jobs for scalability and cost efficiency. - Implement automation and best practices around CI/CD, testing, deployment, monitoring, and operational support. - Collaborate with cross-functional teams to understand business requirements and translate them into effective technical solutions. - Participate in architecture discussions and contribute to the continuous improvement of the organization's data platform. - Ensure compliance with security, access control, and data governance standards. Required Skills & Qualifications : - 4 to 9 years of relevant experience in Data Engineering with strong hands-on experience in AWS. - Strong proficiency in Python and SQL. - Hands-on experience building and managing ETL/ELT data pipelines. - Strong knowledge of AWS data services such as S3, Glue, Redshift, Athena, EMR, Lambda, Kinesis, or Step Functions. - Experience with PySpark/Spark and distributed data processing. - Good understanding of Data Warehousing, Data Lakes, Data Lakehouse concepts, and dimensional data modelling. - Experience working with relational and/or NoSQL databases. - Understanding of data pipeline orchestration tools such as Apache Airflow, AWS Step Functions, or similar platforms. - Experience with cloud security, IAM, encryption, monitoring, and performance optimization. - Exposure to Git, CI/CD, Docker, and DevOps practices is preferred. - Strong analytical and problem-solving abilities with excellent communication skills. Good to Have : - Experience with Copilot Studio or Microsoft Copilot technologies. - Exposure to developing or integrating AI-powered data solutions, conversational AI, or intelligent automation. - Experience working with APIs, LLM-based applications, or AI/ML data pipelines. - Knowledge of Microsoft technologies such as Power Platform, Power Automate, or Azure services will be an added advantage. - AWS certifications such as AWS Certified Data Engineer, AWS Solutions Architect, or AWS Developer will be a plus.