Senior Data Engineer

If you're a Sr. Data Engineer looking to take on the highest priority project with a ton of compelling data for the premier name/brand in Dallas, look no further! What will set you apart from other Data Engineers is professional experience staging data optimally for AI usage, access rights, rule sets, and visibility controls. You'll be working with a small, world-class team across numerous business units to execute on the first of many enterprise AI enablement projects.

*This implementation phase will be 6-9 months with the possibility of extension or conversion to an FTE for the right person. Due to the nature and priority of this project, you'll be expected to be in the office 4 days a week (1 remote). 3rd party and/or visa required candidates cannot be considered.*

The Data Engineer builds and supports the data warehouse and reporting environment the business relies on for day-to-day decisions. The role sits inside an active data project consolidating reporting and warehouse content across existing platforms, and the work is hands-on: writing SQL, building and loading warehouse tables, developing ETL, automating routine work with scripts, and delivering results to business users through Tableau. Success is measured by whether the numbers are right, the loads run on time, and the people who depend on the reports trust what they see.

ESSENTIAL DUTIES AND RESPONSIBILITIES

• Write, tune, and maintain SQL queries, stored procedures, and views supporting reporting and analysis.
• Build and maintain data warehouse structures, including fact and dimension tables and supporting dimensional models.
• Develop, schedule, and support ETL processes that load data from source systems into the warehouse.
• Build and publish Tableau reports and dashboards, and maintain existing reports as requirements change.
• Write shell scripts to automate routine data movement, file handling, job execution, and operational monitoring tasks.
• Validate data after each load and reconcile results back to source systems to confirm reporting accuracy.
• Research and resolve data issues and reporting discrepancies, tracing problems to root cause.
• Work with analysts and business users to translate reporting requests into data structures, queries, and deliverable reports.
• Document data models, ETL logic, source-to-target mappings, and report definitions.
• Support the ongoing data project, including migrating existing warehouse and reporting content onto current platforms.

JOB REQUIREMENTS: Must meet the following minimum requirements:

• 5+ years of experience in data engineering, data warehousing, ETL development, business intelligence, or a related field.
• Strong SQL skills, including query writing and tuning, stored procedures, and views.
• Proficiency in Python for scripting, automation, and data processing tasks.
• Working knowledge of dimensional data warehouse design, including fact and dimension tables, grain, keys, and slowly changing dimensions.
• Hands-on ETL experience building and supporting production data loads.
• Working knowledge of Tableau, sufficient to build, publish, and maintain standard reports and dashboards.
• Ability to write shell scripts for automation, file handling, and job control in a Linux or Unix environment.
• Experience with Git for source control, including branching, merging, and pull request workflows.
• Strong analytical and problem-solving skills, with demonstrated ability to resolve complex data issues.
• Attention to detail and a consistent habit of validating results before publishing them.
• Excellent communication skills, including the ability to explain technical concepts to non-technical audiences.
• Experience working in agile environments and following established development, testing, and documentation standards.
• Self-motivated and detail-oriented, able to manage multiple priorities and handle confidential information appropriately.
• Availability to work standard business hours with after-hours, event, and occasional weekend support as needed.

PREFERRED QUALIFICATIONS

• Experience with Snowflake.
• Experience with cloud or on-premise data platforms such as AWS, Azure, Vertica, or HPE Data Fabric.
• Experience with job scheduling or orchestration tools such as Airflow, Control-M, or Autosys.
• Experience supporting a data warehouse migration or platform consolidation effort.

DESIRABLE EXPERIENCE

• Experience staging data optimally for AI usage, access rights, rule sets, and visibility controls.