The Role
Designs and supports enterprise-scale data engineering and analytics solutions using SQL, Python, AWS, ETL/ELT, data lakes, and streaming technologies. Builds scalable ingestion and processing pipelines, analytical datasets, automated testing, governance, observability, and CI/CD processes. Partners with Product, AI, Operations, Engineering, Design, and executive stakeholders to resolve data issues and improve platform reliability. The role supports telemetry ingestion, evaluation datasets, AI-related analytics, and future autonomous operations.
Summary Generated by Built In
Department:
TechnologyOur Company Promise
We are committed to provide our Employees a stable work environment with equal opportunity for learning and personal growth. Creativity and innovation are encouraged for improving the effectiveness of Southwest Airlines. Above all, Employees will be provided the same concern, respect, and caring attitude within the organization that they are expected to share externally with every Southwest Customer.
Job Description:
Job Summary
- Work with limited supervision to support data engineering and data analytics solutions. Provide design guidance and implementation for end-to-end analytic solutions. Coordinate with SWA focused groups to create unique data infrastructure, run tests on their designs to isolate errors and update systems to accommodate changes in company needs
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
- Advanced SQL development, data modelling, performance tuning, and enterprise-scale analytical datasets.
- Advanced Python development for reusable data frameworks, automation, testing, and production-grade engineering
- Design and ownership of scalable ETL/ELT architectures, data lake, lakehouse, and enterprise integration patterns.
- Advanced AWS data engineering experience across Glue, S3, Athena, Redshift, EMR, Kinesis, Step Functions, Airflow/MWAA, security, and reliability.
- Data quality, governance, APIs, CI/CD pipelines, observability, automated testing, and production support leadership
- Lead scalable enterprise data engineering foundations supporting Agent Observability, Ops Enablement, and future autonomous operations.
- Own telemetry ingestion, data processing pipelines, evaluation datasets, and reusable data engineering frameworks on AWS.
- Serve as the technical partner across Product, AI, Operations, and Engineering teams while improving platform reliability, governance, and scalability.
Knowledge, Skills and Abilities
- 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 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.
- Advanced SQL development, data modelling, performance tuning, and enterprise-scale analytical datasets.
- Advanced Python development for reusable data frameworks, automation, testing, and production-grade engineering
- Design and ownership of scalable ETL/ELT architectures, data lake, lakehouse, and enterprise integration patterns.
- Advanced AWS data engineering experience across Glue, S3, Athena, Redshift, EMR, Kinesis, Step Functions, Airflow/MWAA, security, and reliability.
- Data quality, governance, APIs, CI/CD pipelines, observability, automated testing, and production support leadership
- Databricks and Apache Spark
- Iceberg, Delta Lake, and Hudi
- Kafka, Kinesis, and streaming architectures
- AI/GenAI telemetry, vector databases, RAG analytics, QuickSight, or Grafana
Education
- Required: Bachelor's degree in Computer Science, Engineering, Information Systems or related field and/or equivalent formal training
Experience
- Required: Intermediate level experience, fully functioning broad 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
- 2-5 years of relevant work-related experience
- Advanced SQL development, data modelling, performance tuning, and enterprise-scale analytical datasets.
- Advanced Python development for reusable data frameworks, automation, testing, and production-grade engineering
- Design and ownership of scalable ETL/ELT architectures, data lake, lakehouse, and enterprise integration patterns.
- Advanced AWS data engineering experience across Glue, S3, Athena, Redshift, EMR, Kinesis, Step Functions, Airflow/MWAA, security, and reliability.
- Data quality, governance, APIs, CI/CD pipelines, observability, automated testing, and production support leadership
- Databricks and Apache Spark
- Iceberg, Delta Lake, and Hudi
- Kafka, Kinesis, and streaming architectures
- AI/GenAI telemetry, vector databases, RAG analytics, QuickSight, or Grafana
Other Qualifications
- Must meet confidentiality expectations as to confidential, proprietary and sensitive Company information
- Ability to work extended hours as needed
- Ability to work onsite approximately 3 days per week and as required by the business.
Southwest Airlines is an Equal Opportunity Employer.
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Skills Required
- Bachelor's degree in Computer Science, Engineering, Information Systems, or a related field, or equivalent formal training
- 2-5 years of relevant work experience
- Intermediate experience with cloud infrastructure and data lakes
- ETL experience ensuring source-to-target data integrity
- Experience with delimited text, fixed-width, XML, JSON, and Parquet file types
- Service Bus ingress and egress configuration or relevant AWS cloud services administration
- Unit testing, code quality tools, CI/CD technologies, security, and container technologies
- Agile development experience, including Agile ceremonies and practices
- Advanced SQL development, data modeling, performance tuning, and enterprise-scale analytical datasets
- Advanced Python development for reusable frameworks, automation, testing, and production engineering
- Scalable ETL/ELT architecture, data lake, lakehouse, and enterprise integration pattern experience
- Advanced AWS data engineering experience with Glue, S3, Athena, Redshift, EMR, Kinesis, Step Functions, Airflow/MWAA, security, and reliability
- Experience with data quality, governance, APIs, CI/CD pipelines, observability, automated testing, and production support leadership
- Databricks and Apache Spark
- Iceberg, Delta Lake, and Hudi
- Kafka, Kinesis, and streaming architectures
- AI/GenAI telemetry, vector databases, RAG analytics, QuickSight, or Grafana
- Ability to work onsite approximately three days per week and as required by the business
- Ability to work extended hours as needed
- Ability to maintain confidentiality of proprietary and sensitive company information
Southwest Airlines Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Southwest Airlines and has not been reviewed or approved by Southwest Airlines.
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Pay Growth & Progression — Pay progression is described as materially improving after major 2024 union agreements, especially for pilots and flight attendants. Compensation satisfaction is framed as stronger over time as step scales and seniority accumulate.
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Retirement Support — Retirement support stands out through a dollar-for-dollar 401(k) match and the presence of profit-sharing contributions that can add to retirement savings. Stock purchase access is also positioned as an additional ownership-oriented component of total rewards.
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Wellbeing & Lifestyle Benefits — Wellbeing and lifestyle value is elevated by extensive space-available travel privileges and broad travel-related discounts that can materially offset personal travel costs. Recognition mechanisms like points-based rewards are also positioned as an added lifestyle-oriented perk.
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The Company
What We Do
At Southwest Airlines we connect People to what’s important in their lives—that also means connecting our Employees to what’s important in their lives! Our Employees value the opportunity to work hard, be creative, and have fun on the job. Southwest Airlines recognizes, respects, and values differences. By fostering a culture that embraces and utilizes our diversity, we create competitive advantages in teamwork and innovation that contribute to our overall success.
