AWS Data Engineer
Apply NowCompany: Futran Tech Solutions Pvt. Ltd.
Location: Austin, TX 78745
Description:
Role: AWS Data engineer
It is a hybrid model. Tuesday to Thursday in office and remote for the other 2 days.
Location: Chicago, Madison NJ, Austin TX or in Irvine CA.
Looking for a strong AWS Data Engineer who has hands on experience with AWS data stack (AWS Glue, Glue Catalog, S3, AWS Hudi, EMR, Appflow and airflow). Successful candidate will be responsible for the following activities:
i. Identify, Build the foundational blocks of the Data Lake Platform such as Processing layer, CI/CD pipelines, Orchestration, template pipeline etc.
ii. Work closely with Infrastructure/Architects/key stakeholders to finalize the foundational blocks on various aspects of the platform
iii. Automate pipeline for Moxie data source by using the foundation that is built on.
iv. Work with Business stakeholders to understand the data needs and build data tech debt.
v. Build reusable data pipelines/framework as a solution accelerator
vi. Configure automated pipelines using the framework for the data sources (CC1, MedForce, Nice).
vii. Build Data Quality/Governance framework to make data complete and trustworthy.
viii. Reference Architecture, Documentation of Data Platform
ix. Configure automated pipelines for the data sources identified from tech debt.
x. Production roll-out, knowledge sharing and hyper-care
It is a hybrid model. Tuesday to Thursday in office and remote for the other 2 days.
Location: Chicago, Madison NJ, Austin TX or in Irvine CA.
Looking for a strong AWS Data Engineer who has hands on experience with AWS data stack (AWS Glue, Glue Catalog, S3, AWS Hudi, EMR, Appflow and airflow). Successful candidate will be responsible for the following activities:
i. Identify, Build the foundational blocks of the Data Lake Platform such as Processing layer, CI/CD pipelines, Orchestration, template pipeline etc.
ii. Work closely with Infrastructure/Architects/key stakeholders to finalize the foundational blocks on various aspects of the platform
iii. Automate pipeline for Moxie data source by using the foundation that is built on.
iv. Work with Business stakeholders to understand the data needs and build data tech debt.
v. Build reusable data pipelines/framework as a solution accelerator
vi. Configure automated pipelines using the framework for the data sources (CC1, MedForce, Nice).
vii. Build Data Quality/Governance framework to make data complete and trustworthy.
viii. Reference Architecture, Documentation of Data Platform
ix. Configure automated pipelines for the data sources identified from tech debt.
x. Production roll-out, knowledge sharing and hyper-care