Sr Spec, Data Architect

Job Title: Sr. Specialist, Data Architect Job Code: 46368 Job Location: Salt Lake City, Utah Job Schedule: 9/80 – Employees work 9 out of every 14 days- totaling 80 hours worked- and have every other Friday off

Job Description:

As a member of the Data Analytics team, you will support efforts to solve important business problems, help internal departments make informed decisions, and deliver analytical insights to the business. We are seeking an experienced Data Architect / AI/ML Solutions professional who can work closely with business stakeholders and technical teams to translate business needs into effective data and analytics solutions.

The ideal candidate will have experience supporting analytics, AI/ML, and data solution initiatives, with strong skills in stakeholder communication, requirements gathering, solution development, and cross-functional collaboration. This individual will be responsible for understanding business requirements, identifying opportunities to apply data, analytics, and AI/ML technologies, and contributing to the design and implementation of solutions that support business objectives.

Essential Functions:

Core Capabilities

Strong proficiency in data engineering languages such as Python, SQL, Java, or Scala

Proficiency in large scale data processing engines including but not limited to Spark, Flink, and Snowflake

Prior experience as a data Engineer, software engineer, or similar technical data professional

Hands-on experience with orchestration and pipeline tools like Apache Airflow, Azure Data Factory, Prefect, FiveTran, or Mage

Knowledge of ANSI SQL and data manipulation/query development.

Experience with cloud-based AI/ML platforms (e.g., AWS bedrock, Azure Foundry, etc.).

Open-source AI/ML solutions (various)

Experience with Agile software development (i.e., Jira and Confluence)

Experience in government, defense, or a related regulated sector

Relevant certifications in data, analytics, cloud, or project delivery are beneficial.

Solution Mapping and Design

Assist in evaluating and identifying appropriate data, analytics, and AI/ML approaches that align with business requirements.

Contribute to the design of scalable and practical analytics solutions that support business goals.

Team Player

A strong desire to be a Team player and build a happy collaborative environment.

Mentoring and support for Junior engineers and data scientists

Strong communication skills, both written and verbal.

Solid software engineering skills, including version control (e.g., Git), continuous integration, and automated testing.

Possess a very strong understanding of python and SQL for data ingestion, transformation, and pipelining.

Hands on knowledge of batch and stream processing (Kinesis & Kafka) for large scale data pipelines.

knowledge of architecture and cloud platforms, preferably AWS and Azure

Proactive mindset with a passion for continuous learning and improvement.

Familiarity with containerization technologies such as Docker and Kubernetes.

Experience with Apache Airflow (MWAA), AWS EKS, AWS RDS Aurora (MySQL),

Data observability tools such as Datahub Mote Carlo, Dynatrace, or Great Expectations

Experience building AWS and Azure infrastructure.

Certifications in AWS, Azure, or other relevant platforms.

Key Responsibilities:

Design, develop, and maintain scalable and reliable data pipelines using tools such as Airflow, Python, SQL, and Databricks DLT.

Collaborate closely with data scientists, analysts, and other stakeholders to ensure that data is accessible, consistent, and reliable.

Work with both structured and unstructured data sources to ingest, transform, and store data in a manner that meets business requirements.

Implement effective data modeling and database design to support analytic and operational use cases.

Ensure best practices in data security, data quality, and data governance.

Optimize and tune SQL queries and database performance for high-concurrency environments.

Collaborate with software engineering and analytics engineering teams to integrate data pipelines with application systems.

Leverage cloud platforms (AWS & Azure) to design and deploy data solutions that are scalable, cost-effective, and meet the organization’s needs.

Act as a mentor and provide guidance to junior data engineers, promoting skill growth within the team.

Quality and Validation

Participate in validation, testing, and review of analytics and AI/ML solutions to ensure they meet business and performance requirements.

Support data quality, consistency, and governance practices within assigned solutions.

Technology Awareness

Stay informed about the latest developments in AI/ML technologies and industry best practices.

Assess new tools and technologies for potential application within the organization.

Qualifications:

Bachelor’s Degree and minimum 6 years of prior relevant experience. Graduate Degree and a minimum of 4 years of prior related experience. In lieu of a degree, minimum of 10 years of prior related experience.

Bachelor’s degree in Data Science, Computer Science, Mathematics, Engineering, or related field.

4+ years of experience in data science, advanced analytics, data analysis, or related role.

Preferred Additional Skills:

Strong knowledge of AI/ML concepts and common models such as regression, classification, clustering, and deep learning.

Proven experience in requirement gathering, solution design, and project management.

Strong communication skills with the ability to convey technical concepts to non-technical audiences.

Strong problem-solving skills and a proactive approach to identifying and addressing business challenges.

Experience with programming languages and tools commonly used in AI/ML workflows (e.g., Python, R, SQL).

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