Sr. AWS Data Engineer
Role summary
A leading Hospitality Corporation is seeking a Senior AWS Data Engineer to design, build, and maintain scalable data structures and pipelines within their AWS environment. This role involves integrating internal and external data sources, developing robust data models to support business intelligence and analytics, and ensuring data quality, governance, and security. The engineer will collaborate with cross-functional teams, optimize performance, and troubleshoot data issues, requiring strong proficiency in SQL, Python, and AWS data services, with experience in Databricks and infrastructure-as-code tools being advantageous.
**Visa Status:
*US Citizen or Green Card Only - Client is unable to transfer/sponsor any Visa's***
**Location:
*Irving, TX (Local Candidates Only)***
**Employment Type:
*Full-time / Direct Hire***
**Work Environment:
*Hybrid (Monday thru Thursday - in office / Friday - at home)***
The AWS Senior Data Engineer will own the planning, design, and implementation of data structures for this leading Hospitality Corporation in their AWS environment. This role will be responsible for incorporating all internal and external data sources into a robust, scalable, and comprehensive data model within AWS to support business intelligence and analytics needs throughout the company.
Responsibilities:
- Collaborate with cross-functional teams to understand and define business intelligence needs and translate them into data modeling solutions
- Develops, builds and maintains scalable data pipelines, data schema design, and dimensional data modelling in Databricks and AWS for all system data sources, API integrations, and bespoke data ingestion files from external sources. Includes Batch and real-time pipelines.
- Responsible for data cleansing, standardization, and quality control
- Create data models that will support comprehensive data insights, business intelligence tools, and other data science initiatives
- Create data models and ETL procedures with traceability, data lineage and source control
- Design and implement data integration and data quality framework
- Implement data monitoring best practices with trigger based alerts for data processing KPIs and anomalies
- Investigate and remediate data problems, performing and documenting thorough and complete root cause analyses. Make recommendation for mitigation and prevention of future issues.
- Work with Business and IT to assess efficacy of all legacy data sources, making recommendations for migration, anonymization, archival and/or destruction.
- Continually seek to optimize performance through database indexing, query optimization, stored procedures, etc.
- Ensure compliance with data governance and data security requirements, including data life cycle management, purge and traceability.
- Create and manage documentation and change control mechanisms for all technical design, implementations and systems maintenance.
Target Skills and Experience
- Bachelor's or graduate degree in computer science, information systems or related field preferred, or similar combination of education and experience
- At least 4 years’ experience designing and managing data pipelines, schema modeling, and data processing systems.
- Experience with Databricks a plus (or similar tools like Microsoft Fabric, Snowflake, etc.) to drive scalable data solutions.
- Experience with SAP a plus
- Proficient in Python, with a track record of solving real-world data challenges.
- Advanced SQL skills, including experience with database design, query optimization, and stored procedures.
- Experience with Terraform or other infrastructure-as-code tools is a plus.
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