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Tech Stack
Tools & technologiesHadoopPythonSparkSQLTableau
About the role
Key responsibilities & impact- Implement automated data quality checks, validation rules, and anomaly detection at each stage of the data pipeline to prevent corrupt, incomplete, or biased data from reaching AI models
- Define and enforce data quality SLAs (e.g., completeness, timeliness, consistency, accuracy thresholds)
- Build monitoring and alerting systems to detect pipeline failures, data drift, and schema changes that could degrade AI model performance
- Conduct root cause analysis on data quality incidents and implement preventative controls
- Implement and maintain end-to-end data pipelines, including processes for structured, semi-structured, unstructured datasets
- Work with AI Deployment Engineers to optimize data pipelines for AI model training and data stores for AI model retention
- Ensure data availability and reliability across operational AI systems
- Implement data retention, data lineage, and other data governance standards across various data pipelines and products
- Collaborate with both technical and non-technical teams for seamless data integration with automation tools
- Implement both batch and real-time/streaming data pipelines to support diverse AI and/or automation use cases
Requirements
What you’ll need- Bachelor’s or Master’s degree in Business Analytics, Data Engineering, Data Science, or another similar field
- 8+ years of experience in related field, such as Data Engineer, Automation Platform Architect, or the like
- Proficiency in Python, SQL, and big data frameworks (Hadoop, Spark)
- Familiarity with tools such as Snowflake, dbt, FiveTran, and Tableau
- Familiarity with GDPR, CCPA/CPRA, and other data privacy regulations
- Understanding of data governance and security compliance, specifically focused on how to maintain at scale with AI solutions
- Effective communication to align data processes with business needs
- Previous background in management consulting is a plus
- Strong business acumen and understanding of enterprise-level processes and the interplay between functions, namely digital, data, and functional teams
- Strong attention to detail, a constantly analytical mindset, and the ability to work independently and effectively to deliver value.
Benefits
Comp & perks- Health insurance
- Flexible work arrangements
- Professional development opportunities
ATS Keywords
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Hard Skills & Tools
PythonSQLHadoopSparkdata quality checksdata validation rulesanomaly detectiondata governancedata pipelinesdata lineage
Soft Skills
effective communicationstrong attention to detailanalytical mindsetbusiness acumenability to work independentlycollaborationproblem-solvingroot cause analysispreventative controlsalignment with business needs