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Minimum 3 years of hands-on experience implementing AI/ML solutions and platform tooling for Data Science. Infrastructure Operations: Minimum 3 to 7+ years of hands-on experience in some combination of the following technologies: Azure (VMs, Web Apps, Managed Databases), GitHub Actions, Terraform, Packer, Airflow, Docker, Kubernetes, Linux/Windows VM administration, Shell scripting (primary Bash but PowerShell as well.
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FM Global is seeking a Machine Learning Operations Data Engineer II to join our AI/ML team to support Machine Learning Engineering, working very closely with Data Science, Data Engineering, Subject Matter Experts and Solution Architecture teams.
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Hands-on production experience with orchestration systems such as Airflow. Expanding, scaling, and standardizing the core foundational principles through consistent observability, lineage, data quality, logging, and alerting across all engineering teams in the Data organization is imperative to the creation of a single pane of glass.
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2+ years of data engineering experience developing large data pipelines. As a member of the Data Capture team you will establish the foundational set of core platform frameworks and pipelines which are a vital key to success - enabling dozens of engineering and analytical teams to unlock the power of data to drive key business decisions and provide engineering, analytics, and operational teams the critical information necessary to scale the largest streaming service.
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Ensure high operational efficiency and quality of the Data Capture platform datasets to ensure our solutions meet SLAs and project reliability and accuracy to all our stakeholders (Engineering, Data Science, Operations, and Analytics teams.
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Hands-on production environment experience with distributed processing systems such as Spark. Architect, design, and code shared libraries in Scala and Python that abstract complex business logic to allow consistent functionality across the Data organization.
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The Data Capture team for the Data organization within the DE&ET organization is in search of a Lead Software Engineer. Maintain detailed documentation of your work and changes to support data quality and data governance requirements.
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5+ years of software engineering experience developing backend applications. Extend functionality of current Data Capture platform offerings, including metadata parsing, extending the metastore API, and building new integrations with APIs both internal and external to the Data organization.
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Implement the Lakehouse architecture, working with customers, partners, and stakeholders to shift towards a Lakehouse centric data platform. Familiarity with Data Modeling techniques and Data Warehousing standard methodologies and practices.
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Contribute to maintaining, updating, and expanding the existing Data Capture platform including the Spark data pipelines while maintaining strict uptime SLAs. The base pay actually offered will take into account internal equity and also may vary depending on the candidate’s geographic region, job-related knowledge, skills, and experience among other factors.
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Provide mentorship and guidance for team members; evangelize the platform, best-practices, data driven decisions; identify new use cases and features and drive adoption. A bonus and/or long-term incentive units may be provided as part of the compensation package, in addition to the full range of medical, financial, and/or other benefits, dependent on the level and position offered.
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The Data Capture team is seeking to grow their team of world class Software Engineers that share their charisma and enthusiasm for making a positive impact. Collaborate with product managers, architects, and other engineers to drive the success of the Data Capture platform.
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Deep understanding of data governance policies, implementation best practices and hands-on experience in implementing Policies as Code Architecture, design & implementation of unified data access using AWS Lake formation, AWS Data Zone, IAM, OKTA and others.
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Hands on experience in data engineering desired with extensive knowledge of SQL and PySpark, on Databricks Platform. Hands on experience designing, building, and optimizing data pipelines, architecture for large scale data warehousing projects.
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Strong proficiency in data pipeline and ETL design, with hands-on experience in tools like Apache Airflow, Apache NiFi, or similar. Familiarity with modern cloud platforms (e.g., AWS, GCP, Azure) and their data engineering services.
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hands on data engineering jobs Title: architect lead data in Columbia, Missouri
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