Data Engineer III

Love's Travel Stops & Country Stores, Inc.•Houston, TX

43d•Onsite

About The Position

The Data Engineer III will play a pivotal role in building, managing, and optimizing data pipelines for the Enterprise Data & Analytics initiatives following industry standard practices and tools. This role will be the key interface in operationalizing data and analytics on behalf of the business unit(s) and organizational outcomes.

Requirements

HS Diploma or equivalent required, bachelor's degree in business with MIS or technology related degree (C.S.) preferred
3-5 years experience with cloud data warehouses such as Snowflake, working with complex SQL code, working with DevOps capabilities like version control, automated builds, testing and release management using tools like Git
Moderate experience working with open-source or commercial message queuing technologies, such as Azure Service Bus, Apache Nifi, Apache Kafka, etc., and with replication software such as Fivetran or HVR
Strong experience with various Data Management architectures like Data Warehouse, Data Lake, Data Hub, Data Vault and the supporting processes like Data Integration, Governance, and Metadata Management
Strong experience working with large, heterogeneous datasets in building data pipelines and integrating datasets using traditional data integration technologies, including ETL/ELT, data replication/CDC, message-oriented data movement, and API-based data acquisition

Nice To Haves

SQL Server 2008+, SAP Hana, Tableau, Power BI, R/Python, and Dbt experience preferred

Responsibilities

Architect, build, and maintain data pipelines through acquisition, ingestion, staging, and modeling
Provide architectural input to program leadership for project teams to develop solutions that align with long-term data warehouse strategy
Responsible for the identification and qualification of source data to satisfy master and transactional data requirements for the target warehouse
Lead data assessment and mapping activities, and develop the underlying migration framework to extract, transform, validate, enrich, and load the source data
Define reusable solution architectures using standard modeling practices
Design and deliver solutions that are reliable and scalable and focused on driving automation and improving productivity
Fundamental understanding of data warehousing principles
Ability to understand impacts of a solution architecture on corresponding design, build, and test efforts