Blue Origin
Senior Data Engineer
Blue Origin, Seattle, Washington, us, 98127
At Blue Origin, we envision millions of people living and working in space for the benefit of Earth. We’re working to develop reusable, safe, and low-cost space vehicles and systems within a culture of safety, collaboration, and inclusion. Join our diverse team of problem solvers as we add new chapters to the history of spaceflight!We are looking for someone to apply their technical expertise, leadership skills, and commitment to quality to positively impact safe human spaceflight. Passion for our mission and vision is required!This role is part of Enterprise Technology (ET), where we’re developing the digital infrastructure needed to build the road to space, with an emphasis on digital capabilities required to advance Blue Origin’s mission. Enterprise Technology is the center of excellence for digital technology at Blue Origin, providing oversight and governance to align technology and business strategies.We are seeking a highly skilled Senior Data Engineer with preferable experience in data platforms to join our dynamic team. This role is crucial in advancing our data capabilities for aerospace manufacturing, enabling us to drive innovation and efficiency across our organization.Key Responsibilities:
Data Ingestion and Ontology/Canonical Model Creation:Design and develop data ingestion templates and ETL processes for operational & analytical data platforms.Create and maintain an ontology structure tailored to aerospace manufacturing data requirements.Metadata Driven Data Pipelining:Build and promote reusable data ingestion and ETL templates to facilitate data publishing and federation across teams in the enterprise.Data Application Development and Support:Collaborate with domain consumers/leads to build domain-specific data applications for viewing knowledge graphs, creating and orchestrating events on the Ontology or canonical models.Data Reconciliation:Implement solutions for data reconciliation with various data sources to ensure data accuracy and consistency.Monitoring and Performance:Develop and maintain monitoring & observability solutions to track data pipeline statistics and ensure data quality.Monitor data platform usage and optimize as needed.Data Management Controls:Solution and implement data management controls including data quality, role based access, data classification & data archiving as part of data ingestion and building the Ontology.DataOps:Implement DataOps best practices to streamline data pipeline deployment and management.Develop & maintain monitoring solution to track data pipeline statistics and enable proactive issue detection and resolution.Mentorship and Knowledge Sharing:Provide mentorship to junior data engineers and assist in their skill development.Decompose complex data integration problems into known patterns for execution by junior team members.Technology Stack Experience
Programming Languages - Python, PySpark, Java, SQLDatabases - Postgres, OracleCloud Services – AWS, Azure, GCP (storage, compute, databases, catalogs, streaming, replication, Queueing & Notification, Logging & Monitoring service) – any one of the cloud platforms is good but AWS is preferred.Big Data FrameworksMetadata Catalogs – DataHub, Informatica, Collibra (experience in any one is good)Data Quality Platforms – Anomolo, Informatica, BigEye (experience in any one is good)Event Platforms – Kafka, MSKData Platforms – Palantir Foundry, Databricks, Snowflake (experience in any one is good)Qualifications:
Bachelor's or Master's degree in Computer Science, Data Engineering, or a related field.Proven experience as a Data Engineer, with a strong focus on data platforms like Databricks, Snowflake or Palantir Foundry.Minimum experience required in the data engineering & data management: 8 – 12 years.Extensive knowledge of data ingestion, ETL processes, and data modeling.Strong problem-solving skills and the ability to work with complex data integration challenges.Experience with data reconciliation, data pipeline & data monitoring, and performance optimization.Excellent communication and teamwork skills.Leadership experience and the ability to mentor junior engineers.Prior experience in aerospace manufacturing or a related industry is a plusAbility to earn trust, maintain positive and professional relationships, and contribute to a culture of inclusionMust be a U.S. citizen or national, U.S. permanent resident (current Green Card holder), or lawfully admitted into the U.S. as a refugee or granted asylum.
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Data Ingestion and Ontology/Canonical Model Creation:Design and develop data ingestion templates and ETL processes for operational & analytical data platforms.Create and maintain an ontology structure tailored to aerospace manufacturing data requirements.Metadata Driven Data Pipelining:Build and promote reusable data ingestion and ETL templates to facilitate data publishing and federation across teams in the enterprise.Data Application Development and Support:Collaborate with domain consumers/leads to build domain-specific data applications for viewing knowledge graphs, creating and orchestrating events on the Ontology or canonical models.Data Reconciliation:Implement solutions for data reconciliation with various data sources to ensure data accuracy and consistency.Monitoring and Performance:Develop and maintain monitoring & observability solutions to track data pipeline statistics and ensure data quality.Monitor data platform usage and optimize as needed.Data Management Controls:Solution and implement data management controls including data quality, role based access, data classification & data archiving as part of data ingestion and building the Ontology.DataOps:Implement DataOps best practices to streamline data pipeline deployment and management.Develop & maintain monitoring solution to track data pipeline statistics and enable proactive issue detection and resolution.Mentorship and Knowledge Sharing:Provide mentorship to junior data engineers and assist in their skill development.Decompose complex data integration problems into known patterns for execution by junior team members.Technology Stack Experience
Programming Languages - Python, PySpark, Java, SQLDatabases - Postgres, OracleCloud Services – AWS, Azure, GCP (storage, compute, databases, catalogs, streaming, replication, Queueing & Notification, Logging & Monitoring service) – any one of the cloud platforms is good but AWS is preferred.Big Data FrameworksMetadata Catalogs – DataHub, Informatica, Collibra (experience in any one is good)Data Quality Platforms – Anomolo, Informatica, BigEye (experience in any one is good)Event Platforms – Kafka, MSKData Platforms – Palantir Foundry, Databricks, Snowflake (experience in any one is good)Qualifications:
Bachelor's or Master's degree in Computer Science, Data Engineering, or a related field.Proven experience as a Data Engineer, with a strong focus on data platforms like Databricks, Snowflake or Palantir Foundry.Minimum experience required in the data engineering & data management: 8 – 12 years.Extensive knowledge of data ingestion, ETL processes, and data modeling.Strong problem-solving skills and the ability to work with complex data integration challenges.Experience with data reconciliation, data pipeline & data monitoring, and performance optimization.Excellent communication and teamwork skills.Leadership experience and the ability to mentor junior engineers.Prior experience in aerospace manufacturing or a related industry is a plusAbility to earn trust, maintain positive and professional relationships, and contribute to a culture of inclusionMust be a U.S. citizen or national, U.S. permanent resident (current Green Card holder), or lawfully admitted into the U.S. as a refugee or granted asylum.
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