Data Engineer: End-to-End Pipelines & Cloud

Lockheed Martin; Lexington (KY); In loco; USD 94.000 - 175.000; Tempo pieno

Vantaggi offerti da questo lavoro

Medical

Dental

Vision

Flexible work arrangements

401(k) match

Paid time off

Holidays

Parental Leave

EAP

Flexible Spending Accounts

Education Assistance

Life Insurance

Short-Term Disability

Long-Term Disability

Annual incentive programs

Descrizione del lavoro

Lockheed Martin seeks a data solutions professional to deliver full-stack data across the processing pipeline, applying systems engineering to collect, ingest, process, store, and deliver data at scale and speed. You will work with local, distributed, and cloud technologies plus data virtualization and smart caching.

Responsibilities include building pipelines, designing secure data solutions, and managing the lifecycle from analysis to ETL, reporting, and analytics while maintaining performance

Mansioni

• Build data pipelines that clean, transform, and aggregate unorganized data into databases or data sources that are ready for analysis
• Design and implement data solutions by defining functional capabilities, security, back-up, and recovery specifications
• Work through all stages of a data solution lifecycle, e.g., analyze / profile data, create conceptual, logical and physical data model designs, architect and design ETL, reporting and analytics
• Maintain data systems performance by identifying and resolving production and application development problems; calculating optimum values for parameters; evaluating, integrating, and installing new releases; Define standards, best practices, and certification processes for data objects

Descrizione del lavoro

Lockheed Martin seeks a data solutions professional to deliver full-stack data across the processing pipeline, applying systems engineering to collect, ingest, process, store, and deliver data at scale and speed. You will work with local, distributed, and cloud technologies plus data virtualization and smart caching.

Responsibilities include building pipelines, designing secure data solutions, and managing the lifecycle from analysis to ETL, reporting, and analytics while maintaining performance