Job Description

Must Haves:

Candidates must be willing to work on W2, no C2C.
5+ years of data engineering experience specifically developing large-scale data pipelines.
Databricks and Python expertise.

Qualifications:

5+ years of data engineering experience developing large data pipelines
Proficiency in at least one major programming language.
Expertise on databricks and Python.
Hands-on production environment experience with distributed processing systems such as Spark
Hands-on production experience with data pipeline orchestration systems such as Airflow for creating and maintaining data pipelines
Experience with at least one major Massively Parallel Processing (MPP) or cloud database technology (Snowflake, Databricks, Big Query).
Experience in developing APIs with GraphQL
Advanced understanding of OLTP vs OLAP environment.
Strong background in at least one of the following: distributed data processing or software engineering of data services, or data modeling

Key Responsibilities:

Contribute to maintaining, updating, and expanding existing Core Data platform data pipelines.
Build and maintain APIs to expose data to downstream applications.
Develop real-time streaming data pipelines.
Tech stack includes Airflow, Spark, Databricks, Delta Lake, and Snowflake.
Collaborate with product managers, architects, and other engineers to drive the success of the Core Data platform.
Contribute to developing and documenting both internal and external standards and best practices for pipeline configurations, naming conventions, and more.
Ensure high operational efficiency and quality of the Core Data platform datasets to ensure our solutions meet SLAs and project reliability and accuracy to all our stakeholders.