Data Engineer

Job Title: Data Engineer

Company Description

Utah Tech Labs (UTL) specializes in digital transformations, offering technology solutions that help businesses build their digital vision. By turning IT into a strategic asset, UTL enables organizations to operate as autonomous enterprises. Their expertise extends to addressing business challenges in automation, service management, and operations. UTL is driven by a forward-thinking approach to deliver sustainable innovation.

Job Overview:

Data Wirehouse

Key Responsibilities:

• Design and implement a scalable Data Wirehouse architecture using Databricks and comparable data processing platforms.
• Build, maintain, and optimize ETL/ELT pipelines for ingesting and transforming data from diverse sources.
• Enable storage and distribution of processed data across multiple relational and analytical data stores.
• Develop data transformations using Spark-based frameworks (PySpark, Spark SQL) and SQL.
• Ensure data accuracy, quality, and consistency through validation, monitoring, and alerting mechanisms.
• Optimize pipeline performance, resource usage, and query execution for large-scale datasets.
• Collaborate with data analysts, backend engineers, and stakeholders to align data models with business needs.
• Create and maintain technical documentation for data architecture, pipelines, and workflows.

Technical Skills & Expertise:

• Data Processing Platforms:

  Experience with Databricks and similar distributed data processing and analytics tools.

• ETL / ELT Development:

  Strong background in designing and managing scalable data pipelines.

• Databases & Storage Systems:

  Experience working with relational and structured data stores commonly used for transactional and analytical workloads.

• Data Transformation:

  Proficiency in PySpark, Spark SQL, and advanced SQL for data transformation and aggregation.

• Data Integration:

  Familiarity with ingesting data from APIs, files, and batch/streaming sources.

• Performance & Scalability:

  Ability to tune Spark jobs, pipelines, and data storage for performance and cost efficiency.

• Cloud Ecosystems:

  Experience deploying and operating data engineering workloads on cloud platforms.

Industry Experience:

• Analytics & Reporting:

  Building reliable data foundations for dashboards, reports, and business insights.

• Enterprise Data Platforms:

  Integrating data from multiple operational systems into a unified data layer.

• Scalable Data Systems:

  Handling high-volume, structured and semi-structured datasets efficiently.

Preferred Qualifications:

• Bachelor’s degree in Computer Science, Data Engineering, or a related field.
• 3+ years of experience in data engineering, ETL/ELT pipeline development, and data platform design.
• Hands-on experience with Databricks or comparable big data processing frameworks in production.
• Strong SQL expertise and experience working with widely used relational database technologies.
• Understanding of data modeling, data governance, and best practices for maintainable data systems.

Key Competencies:

• Strong problem-solving and analytical thinking skills.
• Clear written and verbal communication abilities.
• Ability to work independently as well as collaboratively in cross-functional teams.
• Adaptability to new tools, technologies, and evolving data requirements.