Azure Data Engineer

Onsite

Hybrid

Either Webcam or In Person Interview

Tax Terms: C2C,W2 And 1099

Skills: Snowflake, DBT, Python, Azure

Overall, 10-12 years' experience as Data Engineer on the Microsoft Azure cloud platform

Snowflake (Columnar MPP Cloud data warehouse), DBT (ETL tool), Python

Deep experience with SQL, database design, optimization, and tuning

Experience designing and implementing Data Warehouse

Strong understanding of Azure services and expertise on Data Lake, Data Factory and Data Bricks

Healthcare industry experience preferred

Experience with open-source relational database (e.g. PostgreSQL, MSSQL, etc.)

Experience in Shell Scripting and one other object-oriented language such as Python, or PhP.

Strong experience in continuous integration and development methodologies tools such as Jenkins, and experience using GitHub.

Experience in an Agile development environment

Programming skills particularly SQL, Shell Scripting, and Python

Good oral and written communication skills

Responsibilities:

Managing data activities such as data requirements gathering, data analysis/modelling, and data issues resolution using standard approved technology

Managing standardization, migration, transformation, validation, and quality assurance of data within multi-database platforms

Leveraging internal and external ETL tools for data processing and publishing

Identifying and maintaining company databases, including data sources, data structures, data organization, and data optimization

Identifying complex issues proactively and is responsible to see them through resolution, including identifying trends through data analysis and manipulation.

Specific client data life cycles from discovery to implementation to maintenance

Formulating and monitors policies, procedures, and standards relating to database management

Responding to production defects and relaying information back to the Operations Manager to communicate with clients.

Contributing to all phases of the data and software development lifecycle when needed

Creating and maintaining code through GitHub repository for change control

Supporting off hours data processing and emergency requests