Job Description
3+ years of experience in AWS Data Engineering. Design and build ETL pipelines & Data lakes to automate ingestion of structured and unstructured data Experience working with AWS big data technologies (Redshift, S3, AWS Glue, Kinesis, Athena ,DMS, EMR and Lambda for Serverless ETL) Should have knowledge in SQL and NoSQL programming languages.
Have worked on batch and real time pipelines. Excellent programming and debugging skills in Scala or Python & Spark. Good Experience in Data Lake formation, Apache spark, python, hands on experience in deploying the models.
Must have experience in Production migration Process Nice to have experience with Power BI visualization tools and connectivity Roles & Responsibilities:
Design, build and operationalize large scale enterprise data solutions and applications Analyze, re-architect and re-platform on premise data warehouses to data platforms on AWS cloud. Design and build production data pipelines from ingestion to consumption within AWS big data architecture, using Python, or Scala. Perform detail assessments of current state data platforms and create an appropriate transition path to AWS cloud. Work Environment Details:Founded in 2011 and trusted by companies across 70 countries and more, we are the skills solutions provider that organizations and individuals the world over count on to innovate faster and create progress.
We help technologists master their craft and take control of their careers.
We empower businesses everywhere to build adaptable teams, speed up release cycles and become scalable, reliable, and secure.
Our mission to democratize technology skills is what drives us, and our values are at the helm of how we work together.
We thrive in an environment with creativity around every corner, challenges that keep us on our toes, and peers who inspire us to be the best we can be.
If you have the development skills required and are excited to come to work every day knowing you’re helping our customers build the skills that power innovation, we want to hear from you!