Yeah! Global
Senior Data Engineer
Yeah! Global, San Francisco, California, United States, 94199
Note: This position might offer visa sponsorship for the right candidate.One of our clients is on the hunt for a Senior Data Engineer to bolster fundamental data models and infrastructure. You’ll be instrumental in fortifying our real-time and data annotation pipelines, analytics warehouse, MLOps, real-time monitoring, and business intelligence reporting.We harness the power of ML/NLP to swiftly detect and safeguard sensitive personal, health, financial, and credential information. Your direct contributions will shape the essence of our product. Collaborating with Engineers, Data Scientists, and Data Analysts, you’ll uphold rigorous technical standards for data management and steer data strategies in both the short and long term. This role is a hybrid position stationed in our San Francisco office.Responsibilities:
Devise, construct, and take charge of the core data models and infrastructure to govern data throughout the analytics stack, spanning AWS, Kafka, Glue, S3, Snowflake, Cassandra, Cockroach DB, Tableau, and Datadog.Forge tight partnerships with Data Analysts to unleash the data essential for fueling dashboards, ad-hoc analyses, monitoring, and high-caliber decision-making across the organization.Collaborate closely with ML Engineering and Data Science to amplify our data pipelines tailored for machine learning, analytics, and data annotation.Formulate and execute a data quality monitoring system integrating source-to-target data validations and anomaly detection.Partner with Security and Engineering to satisfy data governance prerequisites.Requirements:
Mastery of SQL. Substantial proficiency in Python or equivalent.Over five years of hands-on experience with analytical data warehouses/lakes. Preference for AWS/Snowflake expertise.Over five years of experience in developing data pipelines supporting ML/NLP initiatives. Familiarity with leading MLOps and data annotation platforms is advantageous.Over five years of experience scrutinizing intricate datasets using SQL, fine-tuning queries, collaborating with Data Analysts to automate dashboards (with a nod to Tableau), and conducting ad-hoc analyses that spawn actionable business insights.Bachelor's degree in Computer Science or a related field. Possession of an MS/PhD is a bonus.Familiarity with source code repositories and cloud monitoring tools (with a preference for Datadog).Exceptional communication skills, robust analytical prowess, and the ability to operate autonomously or as part of a team.A knack for thriving in a dynamic environment, exhibiting flexibility, and being willing to dive in and tackle any challenge for success.
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Devise, construct, and take charge of the core data models and infrastructure to govern data throughout the analytics stack, spanning AWS, Kafka, Glue, S3, Snowflake, Cassandra, Cockroach DB, Tableau, and Datadog.Forge tight partnerships with Data Analysts to unleash the data essential for fueling dashboards, ad-hoc analyses, monitoring, and high-caliber decision-making across the organization.Collaborate closely with ML Engineering and Data Science to amplify our data pipelines tailored for machine learning, analytics, and data annotation.Formulate and execute a data quality monitoring system integrating source-to-target data validations and anomaly detection.Partner with Security and Engineering to satisfy data governance prerequisites.Requirements:
Mastery of SQL. Substantial proficiency in Python or equivalent.Over five years of hands-on experience with analytical data warehouses/lakes. Preference for AWS/Snowflake expertise.Over five years of experience in developing data pipelines supporting ML/NLP initiatives. Familiarity with leading MLOps and data annotation platforms is advantageous.Over five years of experience scrutinizing intricate datasets using SQL, fine-tuning queries, collaborating with Data Analysts to automate dashboards (with a nod to Tableau), and conducting ad-hoc analyses that spawn actionable business insights.Bachelor's degree in Computer Science or a related field. Possession of an MS/PhD is a bonus.Familiarity with source code repositories and cloud monitoring tools (with a preference for Datadog).Exceptional communication skills, robust analytical prowess, and the ability to operate autonomously or as part of a team.A knack for thriving in a dynamic environment, exhibiting flexibility, and being willing to dive in and tackle any challenge for success.
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