Description

The Data Assurance Specialist is a highly technical role responsible for ensuring the accuracy, consistency, and integrity of data across multiple systems. This position requires strong hands-on expertise in data tools and technologies, including SQL, Python, and modern data platforms such as Snowflake, to analyze, validate, and remediate data at scale.

The specialist will proactively evaluate data flows between systems to identify inconsistencies, perform root cause analysis, and implement corrective actions through both manual investigation and automated solutions. They will write and optimize queries, develop scripts, and leverage data platforms to detect anomalies, reconcile datasets, and enforce data quality standards.

In addition, the role is responsible for documenting data models, transformations, and business rules to ensure transparency and repeatability. A key focus includes identifying redundant or duplicate data, improving data pipelines, and contributing to the design and build-out of reliable, scalable data sources.

This position partners closely with development teams requiring both technical depth and strong communication skills to translate data issues into actionable solutions. The ideal candidate combines rigorous analytical thinking with practical experience in programming languages.

Responsibilities

• Analyze and validate data across multiple systems to ensure accuracy, completeness, and consistency
• Identify, investigate, and resolve data discrepancies through root cause analysis
• Develop and execute complex SQL queries to audit, reconcile, and monitor data quality
• Build and maintain Python scripts and automated processes to detect anomalies and enforce data integrity at scale
• Work within cloud data platforms such as Snowflake to manage, transform, and validate large datasets
• Monitor and troubleshoot integrations, identifying breaks, delays, or inconsistencies in data flow between systems
• Partner with development and application teams to implement data quality controls and validation frameworks
• Design and maintain data quality dashboards, metrics, and alerts to proactively surface issues
• Identify duplicate, redundant, or unnecessary data and assist with remediation and standardization efforts
• Document data models, mappings, transformations, and business rules to ensure transparency and repeatability
• Assist with the design and development of scalable, governed data models to support analytics and business intelligence applications.
• Collaborate with business stakeholders to understand data requirements and translate them into technical validation rules
• Perform impact analysis for upstream and downstream data changes across integrated systems
• Contribute to data governance initiatives, including defining standards, best practices, and data quality SLAs to support data security, compliance, and integrity as well as implement access control processes
• Work closely across the Company including Sales, Marketing, Business Development, Manufacturing, Quality, Applications, and other business stakeholders to understand data requirements, and deliver effective solutions
• Other duties as required

Qualifications

• Minimum requirement of bachelor's degree in computer science, Data Engineering, or related discipline
• 7+ years of professional experience in data architecture, data engineering, or analytics engineering roles
• 3+ years of hands-on experience with Snowflake (RBAC, masking policies, dynamic tables, resource monitors)
• Proficiency in SQL and data transformation frameworks such as dbt
• Strong knowledge of Kimball dimensional modeling and data warehouse design patterns
• Experience integrating with ERP and MES systems such as Epicor and Camstar
• Familiarity with Power BI, Tableau, or equivalent BI tools
• Working knowledge of data privacy and compliance frameworks (ITAR, SOX, GDPR, etc.)
• Prefer experience with Snowpark or machine learning data pipelines
• Familiarity with SQLFluff or automated SQL linting/validation tools
• Strong understanding of cost governance and monitoring in Snowflake
• Excellent communication and documentation skills, with the ability to bridge business and technical audiences