Data Engineer III

Job Details Level: Experienced

Job Location:

Beusa The Woodlands Corporate Office - The Woodlands, TX 77380

Position Type:
Full Time Education Level: 4 Year Degree

Travel Percentage : up to 10%

Job Shift: Day Data Engineer

Job Description Department:
Data Technology Job Status:
Full TimeFLSA Status:
Salary Exempt

Reports To:

Data Engineering Supervisor

Location:

The Woodlands, TXAmount of

Travel Required:

5-10%

Work Schedule:

Monday–Friday, 8 a.m.–5 p.m.Positions Supervised:
NoneAIP Level: 7

POSITION SUMMARY:

As a Data Engineer at Beusa, you will own the performance, reliability, and cost-efficiency of our Databricks environment. You’ll design and optimize Delta tables, pipelines, and SQL Warehouse workloads so teams get fast, trustworthy data at the lowest reasonable cost. You will collaborate with cross-functional teams to translate requirements into high‑performing, production‑grade datasets and dashboards with clear SLAs.

ESSENTIAL FUNCTIONS:

(The following duties and responsibilities are all essential job functions, as defined by the ADA, except for those that begin with the word "may.")

• Build and operate Lakehouse pipelines on Databricks (Bronze/Silver/Gold) using Delta Lake, Delta Live Tables (DLT), and/or Jobs.
• Own ingestion patterns (Autoloader, CDC, streaming) optimization
• Own data modeling, quality checks, and performance optimization.
• Own performance optimization – profile and tune Spark/SQL workloads: partitioning, clustering, constraints, liquid clustering (if applicable), manage table health.
• Engineer Delta tables for speed and cost: partitioning, Z-Ordering or clustering, constraints, file sizing; manage table health with Auto Optimize, OPTIMIZE, and VACUUM.
• Implement incremental processing patterns (MERGE with Change Data Feed, APPLY CHANGES INTO) with idempotency and exactly-once delivery.
• Partner with data consumers to deliver reliable, well-documented datasets with clear SLAs.
• Design, build, and implement interactive dashboards and reports using Power BI and other visualization tools.
• Collaborate with business units (Operations, Field Engineers, Assets) to gather requirements and translate them into technical solutions.
• Develop and maintain data models, ensuring data quality and integrity.
• Integrate data from multiple sources, including real‑time field equipment and sensors.
• Continuously evaluate and adopt new data management and analytics technologies.
• Educate and support stakeholders on data tools and best practices.
• Advocate for Beusa’s digital transformation and data-driven decision-making.
• Engage with technology vendors and partners as needed.
• Occasional travel to meet with stakeholders.
• Performs other related duties as assigned to assist with successful operations and business continuity.

• Successfully passes background check, pre-employment drug screening, an any pre-employment aptitude and/or competency assessment(s).
• Valid U.S. driver’s license and ability to pass a background check.

• Bachelor’s degree in MIS, Computer Science, Engineering, IT, or related field.
• 7-10+ years of experience in a data-focused role (Business Intelligence, Data Analysis, Data Management, etc.).

• 8+ years of experience in Data Engineering, Data Warehousing, or Analytics Engineering.
• 3+ years of hands‑on experience with Databricks and the Lakehouse Platform.
• Expert‑level proficiency with PySpark, Spark SQL, and distributed data processing concepts.
• Advanced SQL development skills with experience in relational database platforms (Microsoft SQL Server preferred).
• Experience designing and implementing Databricks Medallion Architectures (Bronze, Silver, Gold).
• Experience building and optimizing batch and streaming data pipelines.
• Experience designing, implementing, and maintaining CI/CD deployment strategies for data platforms.
• Experience defining and implementing testing frameworks, including Unit Testing, Data Quality Testing, Schema Validation, Integration Testing, and Regression Testing.
• Experience troubleshooting and optimizing Spark workloads for performance, scalability, reliability, and cost efficiency.
• Experience…