Technical Data Engineer - Level II

About Company:

S&K Technologies, Inc. was formed in 1999 with a vision to become one of the preeminent professional services firms in the country and to provide opportunity and prosperity to the people of the Confederated Salish and Kootenai Tribes (CSKT). Since inception, the S&K Technologies, Inc. enterprise has grown into a family of twelve subsidiary companies that support federal and commercial customers around the world.

OUR MISSION

The S&K Family of Companies is committed to providing the highest quality products and services to our customers in order to deliver the maximum dividend to our shareholder, the CSKT, while ensuring long-term employment, education, and social benefits to our employees, tribal members, and local communities.

About the Role:

This position requires the successful candidate to be able to work on site full time.  Successful consideration is tied to your ability to live within commute distance to the work site.  The Technical Data Engineer - Level II plays a critical role in designing, developing, and maintaining scalable data pipelines and architectures that support the organization's data analytics and business intelligence initiatives. This position focuses on transforming raw data into actionable insights by ensuring data quality, integrity, and accessibility across various platforms. The engineer collaborates closely with data scientists, analysts, and IT teams to optimize data workflows and implement best practices for data management. They are responsible for troubleshooting data-related issues and continuously improving data processing efficiency to meet evolving business needs. Ultimately, this role ensures that the organization’s data infrastructure is robust, reliable, and capable of supporting strategic decision-making processes.

Minimum Qualifications:

• Bachelor’s degree in Computer Science, Information Technology, Engineering, or a related field.
• 3+ years of experience in data engineering or a similar technical role.
• Proficiency in SQL and experience with relational and non-relational databases.
• Hands-on experience with data pipeline and workflow management tools such as Apache Airflow or similar.
• Strong programming skills in languages such as Python, Java, or Scala.
• Experience working with cloud platforms like AWS, Azure, or Google Cloud Platform.
• Familiarity with data warehousing solutions and big data technologies such as Hadoop or Spark.

Preferred Qualifications:

• Master’s degree in a relevant technical field.
• Experience with containerization and orchestration tools like Docker and Kubernetes.
• Knowledge of machine learning pipelines and integration with data engineering workflows.
• Certification in cloud technologies (e.g., AWS Certified Data Analytics, Google Professional Data Engineer).
• Experience with real-time data processing frameworks such as Apache Kafka or Flink.

Responsibilities:

• Design, build, and maintain efficient, reusable, and reliable data pipelines and ETL processes.
• Collaborate with cross-functional teams to understand data requirements and deliver scalable data solutions.
• Monitor and troubleshoot data pipeline performance and data quality issues to ensure accuracy and reliability.
• Implement data integration from multiple sources, ensuring data consistency and integrity.
• Optimize data storage and retrieval processes to improve system performance and reduce latency.
• Document data engineering processes, workflows, and system architecture for knowledge sharing and compliance.
• Stay current with emerging data technologies and recommend improvements to existing data infrastructure.

Skills:

The required skills enable the Technical Data Engineer to build and maintain robust data pipelines that support complex data transformations and integrations. Proficiency in SQL and programming languages like Python allows for efficient querying, manipulation, and automation of data workflows. Familiarity with cloud platforms ensures the engineer can deploy and manage scalable data solutions in modern environments. Preferred skills such as containerization and real-time data processing enhance the ability to develop flexible, high-performance systems that meet dynamic business requirements. Together, these skills empower the engineer to deliver reliable, high-quality data infrastructure that drives informed decision-making across the organization.

SKT, Inc. is an EEO/Veteran/Disabled employer.  For a general description of benefits, please visit: https://www.sktcorp.com/career-center/