Data Engineer

Bachelors degree or higher in the technology field. 4-7 years of experience in the space of data engineering. At least 2-4 years of experience with Snowflake Data warehouse is a must. Recent project work should include usage and deploying production code to Snowflake. Out of touch in Snowflake is not preferred or recommended. At least 2-4 years of experience with Python development is a must. Experience with pyspark, Snowpark apis would be a plus. Experience with basics of data frames and how to around managing data, transformations and using custom sdk s on top of dataframes would be a plus. Ability to write unit tests using pytests or spark testing base would be a plus. Experience in the following areas with Snowflake as datastore would be preferred Managing Data modeling using Liquibase, Managing Data pipelines via SnowSQL / SnowPipe Orchestrating data pipelines within Snowflake or outside of Snowflake. Experience with using/coding data quality frameworks like Soad/Great Expectations etc., Experience with using Airflow / AWS Step functions / Glue / Spark would be preferred and a plus. Experience in one or more below Strong in SQL , SQL Analytics, ELT/ETL ing and Data warehousing. Experience with Azure Synapse / ADF / Cloud ETL tool. (nice to have) Experience with Code Repository, CI/CD , test driven development is preferred. Creating Unit Testing and Automated integration tests is strongly preferred. Experience with multi-cloud AWS/Azure/GCP cloud is a plus. Azure is required/Others preferred. Data processing experience at scale, generating and consuming large feeds. Experience with other cloud data warehouses like Redshift/Azure SQLWH etc., (nice to have). Experience in handling big data at PB scale (nice to have) Experience in dbt, SQL Mesh would be a plus (nice to have) Experience with data governance programs and data offices would be a plus. Exposure to claims, payer, formulary, RWE, EHR/ EMR OR life science, Healthcare data is recommended and would be a plus.