Data Engineer

Description:

We are looking for a Data Engineer to join our Data Engineering Team. The ideal candidate should have a minimum of 3 years of experience with excellent analytical reasoning and critical thinking skills. The candidate will be a part of a team that creates data pipelines that use change data capture (CDC) mechanisms to move data to a cloud provider and then transform data to make it available to Customers to consume. The Data Engineering Team also does general extraction, transformation, and load (ETL) work, along with traditional Enterprise Data Warehousing (EDW) work.

Responsibilities:

Participates in the analysis and development of technical sClientifications, programming, and testing of Data Engineering components.

Participates creating data pipelines and ETL workflows to ensure that design and enterprise programming standards and guidelines are followed. Assist with updating the enterprise standards when gaps are identified.

Follows technology best practices and standards and escalates any issues as deemed appropriate. Follows architecture and design best practices (as guided by the Lead Data Engineer, BI Architect, and Architectural team).

Responsible for assisting in configuration and scripting to implement fully automated data pipelines, stored procedures, and functions, and ETL workflows that allow for data to flow from on-premises Oracle databases to Snowflake where the data will be consumable by our end customers.

Follows standard change control and configuration management practices.

Participates in 24-hour on-call rotation in support of the platform.

Required Skills/Qualifications:

Database Platforms: Snowflake, Oracle, and SQL Server

OS Platforms: Linux OS and Windows Server

Languages and Tools: PL/SQL, Python, T-SQL, StreamSets, Snowflake Streams and Tasks, and Informatica PowerCenter, DBeaver

Drive and desire to automate repeatable processes.

Excellent interpersonal skills and communication, as well as the willingness to collaborate with teams across the organization.

Additional Qualifications:

Experience loading data from files in Snowflake file stages into existing tables.

Experience creating and working with near-real-time data pipelines between relational sources and destinations.

Experience working with StreamSets Data Collector or similar data streaming/pipelining tools (Fivetran, Striim, Airbyte etc...).