Delta Air Lines — Atlanta, Georgia, United States
At Delta, we connect people and cultures, power extraordinary experiences, and shape the future of travel. Here, you'll work on complex challenges on a global scale, using augmented intelligence to build emerging technologies, amplify human potential and continuously grow the skills that keep you at the forefront of what's next. It is an exciting time to be part of Information Technology as Delta continues to modernize how operational data is accessed, trusted, and used to improve reliability, efficiency, and decision-making.
Our team is focused on creating the data foundation, access patterns, and intelligence capabilities needed to connect operational signals across ITSM, telemetry, application, and infrastructure platforms The Senior Data Engineer role supports IT Service Assurance by leading the design and delivery of secure, scalable, and AI-ready data solutions that strengthen operational intelligence, service reliability, automation, and decision-making.
Operating with a high degree of autonomy, this position translates IT operational priorities into trusted data products, reusable integration patterns, and modern engineering capabilities that connect signals across ITSM, CMDB, observability, application, and infrastructure platforms. This role partners across technology, operations, analytics, security, and architecture teams to improve data quality, enable self-service access, advance automation, and create the foundation for reporting, predictive insights, semantic search, and intelligent enterprise solutions • Lead independently across complex data initiatives, proactively identifying improvement opportunities, shaping solutions, and driving delivery from concept through production. • Design and modernize secure, scalable AWS data platforms, pipelines, Lakehouse patterns, and reusable data products aligned to enterprise architecture and governance standards. • Provide senior technical leadership for ingestion, transformation, modeling, metadata, quality, lineage, performance optimization, and production reliability. • Build and optimize batch, incremental, event-driven, and near-real-time integrations across APIs, databases, files, ServiceNow, CMDB, observability, telemetry, and enterprise platforms. • Develop efficient, maintainable Python and SQL for data pipelines, orchestration, transformations, analytics layers, APIs, automation, and reusable engineering frameworks. • Establish trusted data products through automated controls for completeness, accuracy, freshness, reconciliation, monitoring, alerting, and exception handling. • Advance AI-ready architectures that prepare structured and unstructured data for Amazon SageMaker, Amazon Bedrock, LLMs, RAG, vector databases, semantic search, agents, and MCP-enabled solutions. • Design retrieval, embedding, indexing, enrichment, and context-management patterns that improve data usability, discoverability, and responsible AI outcomes. • Drive operational excellence through CI/CD, Infrastructure as Code, automated testing, source control, code reviews, runbooks, production monitoring, and resilient deployment practices. • Apply security, privacy, identity, access control, encryption, retention, data classification, and responsible AI requirements across the data lifecycle. • Influence stakeholders, mentor engineers, promote reusable standards, evaluate emerging technologies, and guide modernization efforts that improve scalability, automation, cost, and business value.
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