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Southwest Airlines
Sr Data Engineer – Analytics & AI
Southwest Airlines
Hyderabad•On-site•5-8 Yrs•2 days ago
Job description
Overview
Department: Technology
Responsibilities
- Assemble large, complex sets of data that meet non-functional and functional business requirements
- Identify, design and implement internal process improvements including re-designing infrastructure for greater scalability, optimizing data delivery, and automating manual processes
- Build required infrastructure for optimal extraction, transformation and loading of data from various data sources using AWS and SQL technologies
- Build analytical tools to utilize the data pipeline, providing actionable insight into key business performance metrics including operational efficiency and customer acquisition
- Work with stakeholders including data, design, product and executive teams and assisting them with data-related technical issues
- Work with stakeholders including the Executive, Product, Data and Design teams to support their data infrastructure needs while assisting with data-related technical issues
- Generate or adapt equipment and technology to serve user needs
- May perform other job duties as directed by Employee's Leaders
- Knowledge of the practical application of engineering science and technology, including applying principles, techniques, procedures, and equipment to the design and production of various goods and services
- Knowledge of design techniques, tools, and principles involved in production of precision technical plans, blueprints, drawings, and models
- Ability to use logic and reasoning to identify the strengths and weaknesses of alternative solutions, conclusions or approaches to problems
- Ability to understand the implications of new information for both current and future problem-solving and decision-making
- Skilled in identifying complex problems and reviewing related information to develop and evaluate options and implement solutions
- Ability to recognize when an issue has occurred or is likely to occur, without needing to diagnose or resolve the problem.
- Ability to combine pieces of information to form general rules or conclusions (includes finding a relationship among seemingly unrelated events)
- Ability to switch efficiently between multiple tasks or information sources, such as spoken instructions, system alerts, or data inputs.
- Ability to organize data or actions in a defined sequence or structure based on specified rules or patterns (e.g., numerical, textual, visual, or mathematical sequences).
- Ability to recognize defined patterns—such as shapes, words, or signals—even when they are embedded within distracting or complex information.
- Preferred:
- Advanced AWS data services and modern data platforms (S3, Glue, Athena, Redshift, Snowflake, or comparable)
- Skilled in designing analytical data models and semantic layers optimized for BI and self-service consumption
- Python and advanced SQL for building analytical datasets and data pipelines
- Databricks or comparable lakehouse platform for analytical data engineering
- Data quality, validation, and reconciliation frameworks for analytical products
- Partnering with Business Data Analysts, AI Engineers, and Product Owners to translate analytical requirements into engineered datasets
- Data pipeline observability and reliability for analytical workloads
- Working knowledge of GenBI, conversational analytics, or AI-enabled analytics dataset requirements
- Knowledge, Skills and Abilities
Qualifications
- Required: Advanced level experience, seasoned and specialized knowledge in:
- Cloud infrastructure, DataLake
- ETL experience ensuring source to target data integrity
- Various filetypes (Delimited Text, Fixed Width, XML, JSON, Parque)
- ServiceBus, setting up ingress and egress within a subscription, or relevant AWS Cloud services administrative experience
- Unit Testing, Code Quality tools, CI/CD Technologies, Security and Container Technologies
- Agile development experience and Agile ceremonies and practices. 5-7 years of relevant work-related experience
- Preferred:
- Building analytical datasets and data pipelines for enterprise BI, GenBI, or AI-enabled analytics consumers
- Delivering on semantic layer, KPI frameworks, or business glossary initiatives
- Databricks, Snowflake, or comparable modern analytics data platform experience
- Vector databases or embeddings pipelines supporting AI-enabled analytics
- Delivering analytical data solutions in Agile environments alongside Business Data Analysts and AI Engineers
- Working across enterprise business domains (Customer, Commercial, Marketing, Brand, Servicing)
- Data platforms serving Analytics, ML, and AI workloads within a large enterprise
- Working across globally distributed analytics and engineering teams
- Must meet confidentiality expectations as to confidential, proprietary and sensitive Company information
- Ability to work extended hours as needed
Education
- Required: Bachelor's degree in Computer Science, Engineering, Information Systems or related field and/or equivalent formal training