Collect, manage and convert raw data into usable information for business analysts

 Improve data reliability and quality by combining raw information from different sources to create consistent and machine-readable formats

 Able to integrate various data types and sources (stream, API, various data formats, file formats) into

AWS environment

 Development of effective processing and ETL pipelines for Automotive, Customer, Web, Sales and

Media Data

 Develop and test architectures that enable data extraction and transformation for predictive or prescriptive modeling

 Data-driven product development in the Customer & Digital Marketing segment

 Conduct complex data analysis and report on results

 Support in turning proof-of-concept projects into production ready and scalable software solutions

 Automation through CI/CD pipelines of the delivery of the data science products in our cloud setting

 Troubleshoot and resolve issues in production environments

You have the following qualifications:

 Preferably completed studies with a relevant specialization in Computer Science or equivalent fields

 3 + years’ Work experience as Data Engineer

 Deep expertise in Python.

 Good hands on experience on AWS Glue, AWS S3, AWS Athena, AWS Redshift,



AWS Lambda, AWS

Step Function, AWS Quicksight & AWS Analytics services.

 Extensive experience in cloud technologies and platforms such as AWS, Azure or Google

 Hands-on experience with containerization technologies like Docker and platforms such as

Kubernetes

 Understanding of DevOps principles and good experience with CI/CD tools (Git, Jenkins, Terraform,

Ansible, CloudFormation, etc.)

 Software development experience.

 Knowledge about web services, APIs, RESTful services

 Basic knowledge of system administration in Linux/Unix or Windows, virtual networking, DNS, TCP/IP etc.

 Experience and knowledge about networking and security in cloud environments

 Data engineering knowledge and experience in tools such as Kafka, Spark streaming, Pentaho Data

Integration, Talend, Apache Hudi, etc.

 SQL and NOSQL database engine knowledge such as Oracle, MySQL, SQLServer, Cassandra,

MongoDB, AWS DynamoDB, AWS Athena, etc.

 Familiar with the concepts of monitoring, metrics, capacity management (Grafana, Prometheus, ELK)

 Robust focus on Code Quality, Robustness, Automation, Testing and Monitoring

📌 Aws Data Engineer (Pune)
🏢 volkswagen-quess
📍 Pune