Galent
Data Governance Alation Analyst Quality and Lineage Data Engineer
Location: San Jose CA Remote
Purpose: Design, build and implement robust data quality and lineage solutions to ensure the integrity, traceability and trustworthiness of data across the Snowflake data platform. This engineering role is critical for maturing data governance, enhancing domain maturity and providing the foundational technical capabilities for data discovery, understanding and reliable consumption.
Key Responsibilities Snowflake data engineering experience is MUST.
Engineer and implement scalable solutions for data cataloging, data dictionary, and data taxonomy ensuring comprehensive and accurate metadata management.
Extract, develop, automate and maintain end‑to‑end data lineage pipelines and processes using Alation for the Snowflake data platform.
Apply deep data engineering expertise to parse and interpret intricate ETL processes, transformation logic, and API definitions to accurately establish and validate data flow and dependencies.
Design and build quantitative metrics, scoring mechanisms and reporting frameworks to assess the quality and coverage of data lineage coverage by domain and subdomain.
Architect and implement advanced data quality solutions moving beyond basic IT monitoring (completeness, timeliness, consistency) to incorporate sophisticated accuracy and validity checks.
Translate complex business rules into executable data quality logic within Snowflake’s internal processes.
Leverage and implement Snowflake native capabilities (e.g., Data Metric Functions, Streamlit, stored procedures, Streams, Tasks, Dynamic Tables) to embed and enforce robust data quality rules directly in the platform from ingestion to downstream consumption.
Develop and maintain the underlying data models and pipelines that feed interactive dashboards and scorecards built with Power BI and Tableau to visualize data maturity, usage, health, lineage completeness and metadata coverage.
Collaborate closely with data domain teams, data engineers and data scientists to identify data quality issues, resolve lineage gaps and improve data trust scores.
Utilize Alation Compose SQL to develop, customize and automate reports specifically for catalog, lineage coverage and data quality insights, integrating the data quality metrics from native Snowflake functions to drive trust flags in Alation.
Contribute to the documentation and visualization of trends in data adoption, metadata completeness, and AI readiness across the organization from an engineering perspective.
Qualifications
7 years of hands‑on engineering experience in data quality, data governance, data lineage or a related data engineering role.
Expert level proficiency in SQL, Python and scripting/automation.
Proven experience designing, building and implementing data quality and metadata management solutions.
Hands‑on experience driving and implementing data lineage initiatives specifically with Alation in conjunction with Snowflake and quality platforms such as Monte Carlo, Attacama, Soda, Octopai, GableAI, etc.
Strong technical understanding of ETL, ELT, pipeline development, API integrations, data modeling and complex data transformation logic.
Deep expertise in Snowflake native data quality features and a track record of implementing them for robust data integrity.
Hands‑on experience with data governance and cataloging tools such as Alation, including practical experience with Alation Compose SQL or similar platforms.
Experience with data visualization tools like Power BI or Tableau for building data quality and lineage dashboards.
Ability to translate business requirements into technical specifications and implement robust scalable data solutions.
Strong problem‑solving skills and attention to detail with a passion for data accuracy and reliability.
Skills
Mandatory Skills:
Snowflake, ANSI‑SQL, Dimensional Data Modeling, Snowflake AI/ML, Snowflake‑Data Science.
Seniority Level Mid‑Senior level
Employment Type Contract
Job Function Consulting
Industries Technology, Information and Internet
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Location: San Jose CA Remote
Purpose: Design, build and implement robust data quality and lineage solutions to ensure the integrity, traceability and trustworthiness of data across the Snowflake data platform. This engineering role is critical for maturing data governance, enhancing domain maturity and providing the foundational technical capabilities for data discovery, understanding and reliable consumption.
Key Responsibilities Snowflake data engineering experience is MUST.
Engineer and implement scalable solutions for data cataloging, data dictionary, and data taxonomy ensuring comprehensive and accurate metadata management.
Extract, develop, automate and maintain end‑to‑end data lineage pipelines and processes using Alation for the Snowflake data platform.
Apply deep data engineering expertise to parse and interpret intricate ETL processes, transformation logic, and API definitions to accurately establish and validate data flow and dependencies.
Design and build quantitative metrics, scoring mechanisms and reporting frameworks to assess the quality and coverage of data lineage coverage by domain and subdomain.
Architect and implement advanced data quality solutions moving beyond basic IT monitoring (completeness, timeliness, consistency) to incorporate sophisticated accuracy and validity checks.
Translate complex business rules into executable data quality logic within Snowflake’s internal processes.
Leverage and implement Snowflake native capabilities (e.g., Data Metric Functions, Streamlit, stored procedures, Streams, Tasks, Dynamic Tables) to embed and enforce robust data quality rules directly in the platform from ingestion to downstream consumption.
Develop and maintain the underlying data models and pipelines that feed interactive dashboards and scorecards built with Power BI and Tableau to visualize data maturity, usage, health, lineage completeness and metadata coverage.
Collaborate closely with data domain teams, data engineers and data scientists to identify data quality issues, resolve lineage gaps and improve data trust scores.
Utilize Alation Compose SQL to develop, customize and automate reports specifically for catalog, lineage coverage and data quality insights, integrating the data quality metrics from native Snowflake functions to drive trust flags in Alation.
Contribute to the documentation and visualization of trends in data adoption, metadata completeness, and AI readiness across the organization from an engineering perspective.
Qualifications
7 years of hands‑on engineering experience in data quality, data governance, data lineage or a related data engineering role.
Expert level proficiency in SQL, Python and scripting/automation.
Proven experience designing, building and implementing data quality and metadata management solutions.
Hands‑on experience driving and implementing data lineage initiatives specifically with Alation in conjunction with Snowflake and quality platforms such as Monte Carlo, Attacama, Soda, Octopai, GableAI, etc.
Strong technical understanding of ETL, ELT, pipeline development, API integrations, data modeling and complex data transformation logic.
Deep expertise in Snowflake native data quality features and a track record of implementing them for robust data integrity.
Hands‑on experience with data governance and cataloging tools such as Alation, including practical experience with Alation Compose SQL or similar platforms.
Experience with data visualization tools like Power BI or Tableau for building data quality and lineage dashboards.
Ability to translate business requirements into technical specifications and implement robust scalable data solutions.
Strong problem‑solving skills and attention to detail with a passion for data accuracy and reliability.
Skills
Mandatory Skills:
Snowflake, ANSI‑SQL, Dimensional Data Modeling, Snowflake AI/ML, Snowflake‑Data Science.
Seniority Level Mid‑Senior level
Employment Type Contract
Job Function Consulting
Industries Technology, Information and Internet
#J-18808-Ljbffr