Sr Data Quality & Observability Engineer (Snowflake)
About The Position
Lamb Weston is modernizing its enterprise data ecosystem to support high-quality analytics, reporting, and decision-making. The Senior Data Quality & Observability Engineer is crucial in ensuring enterprise data is accurate, consistent, reliable, and fit for purpose through measurable data quality and data observability practices. This role requires strong technical data engineering and data analysis skills, business analysis capabilities, and hands-on experience with data quality and observability initiatives. The engineer will collaborate with data engineering, data governance, SAP, and business stakeholders to profile data, define and implement automated quality rules, establish quality SLAs, monitor quality metrics, and resolve data issues at their source. The role involves designing and implementing scalable, reusable data quality controls within Snowflake ELT pipelines and downstream consumption layers. Experience with SAP data is highly valued, as this role will support data quality for SAP master and transactional data integrated into Snowflake and analytics platforms. Expertise in Snowflake or Informatica data quality development, including hands-on implementation of data quality logic using Snowflake SQL and native capabilities, is required.
Requirements
- Bachelor’s degree in Computer Science, Information Systems, Data Analytics, or a related field, or equivalent experience.
- 5+ years of experience in data analysis, data quality, or analytics engineering roles.
- Strong SQL skills and experience working with large, complex datasets.
- Hands-on data quality experience, including implementing data quality logic using SQL and data functions (e.g., window functions, conditional logic, string/date functions, aggregations, table functions/CTEs).
- Demonstrated experience with data profiling, data validation, and data quality frameworks.
- Experience with Git-based version control, code review practices, and deploying changes through SDLC/CI-CD processes.
- Experience working in SAP data environments (ECC, S/4HANA, BW, or HANA)
- Business Analyst skills, including requirements gathering, documentation, and stakeholder facilitation.
- Strong analytical, problem-solving, and communication skills.
- Ability to work collaboratively in cross-functional teams.
Nice To Haves
- Familiarity with cloud data platforms such as Snowflake and AWS preferred.
- Understanding of data governance, metadata, and lineage concepts.
- Ability to travel up to 10 percent.
- Experience supporting Master Data domains such as Customer, Vendor, Material, or Finance.
- Experience with data quality or governance tools.
- Familiarity with Agile delivery methodologies.
- Passion for learning new technologies and continuously improving data quality practices.
Responsibilities
- Design, implement, and maintain data quality rules, checks, and controls across enterprise data assets.
- Perform data profiling, root cause analysis, and anomaly detection across SAP and non-SAP data sources.
- Partner with business stakeholders to understand data quality issues, business impacts, and remediation priorities.
- Translate business requirements into measurable data quality rules and thresholds.
- Develop and maintain data quality frameworks, including reusable SQL patterns, UDFs, stored procedures.
- Implement automated scheduling and orchestration of data quality checks using Snowflake-native capabilities (e.g., tasks, streams) and/or pipeline orchestration tools (ie: Informatica).
- Implement data quality monitoring and observability scorecards, and reporting for key metadata domains.
- Own and evolve enterprise data quality KPIs/scorecards, including standardized definitions, thresholds, and executive-ready reporting across domains.
- Analyze data discrepancies and ensure reconciliation back to systems of record.
- Lead issue management workflows, including defect triage, prioritization, root cause documentation, corrective action validation, and prevention recommendations.
- Contribute to documentation of data quality standards, rules, and operational procedures.
- Assist in user acceptance testing and quality assurance for new or enhanced data assets.
- Provide input and feedback to improve enterprise data quality processes and tooling.
Benefits
- Health Insurance Benefits - Medical, Dental, Vision
- Flexible Spending Accounts for Health and Dependent Care, and Health Reimbursement Accounts
- Well-being programs including companywide events and a wellness incentive program
- Paid Time Off
- Financial Planning Services
- Employee Stock purchase program
- Health Savings Accounts
- Life and Accident insurance
- Family-Friendly Employee events
- Employee Assistance Program services – mental health and other concierge type services
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What This Job Offers
Job Type
Full-time
Career Level
Senior
