Job Details

Data Engineer

Location: Dallas, TX (Remote)

Note: All the interviews are Teams Video & resource must join from Laptop to take up a Tech coding level interview.

Required Skills:

• Extensive experience as Data Engineer with Python Language and Cloud Technologies (AWS preferably).
• Experience in Automating ETL process/Pipelines and AWS Data & Infrastructure with Python.
• Extensive experience with AWS components like S3, Athena, EMR, Glue, Redshift, Kinesis and SageMaker.
• Extensive Experience with SQL/Unix/Linux scripting.
• Developing/testing Experience on Cloud/On Prem ETL Technologies (Ab Initio, AWS Glue, Informatica, Alteryx).
• Experience in Data migration from Onprem to Cloud is Plus.
• Experienced in large-scale application development testing - Cloud/ On Prem Data warehouse, Data Lake, Data Science.
• Extensive experience in DevOps/Data Ops space.
• Having experience in Data Science platforms like SageMaker/Machine Learning Studio/ H2O is plus.

• Work with business stakeholders, Business Systems Analysts and Developers to ensure delivery of Data Applications.
• Building Automation Frameworks using Python.
• Designing and managing the data workflows using Python during development and deployment of data products
• Design, development of Reports and dashboards.
• Analyzing and evaluating data sources, data volume, and business rules.
• Should be well versed with the Data flow and Test Strategy for Cloud/ On Prem ETL Testing.
• Interpret and analyses data from various source systems to support data integration and data reporting needs.
• Experience in testing Database Application to validate source to destination data movement and transformation.
• Work with team leads to prioritize business and information needs.
• Develop and summarize Data Quality analysis and dashboards.
• Knowledge of Data modeling and Data warehousing concepts with emphasis on Cloud/ On Prem ETL.
• Execute testing of data analytic and data integration on time and within budget.
• Troubleshoot & determine best resolution for data issues and anomalies
• Has deep understanding of data architecture & data modeling best practices and guidelines for different data and analytic platforms