{"id":1695151,"url":"https://alion.io/job/southwest-airlines-data-engineer-ai-analytics","title":"Data Engineer - AI & Analytics","company":{"id":1756078,"name":"Southwest Airlines","domain":"southwest.com","url":"https://alion.io/company/southwest-com","size_band":"501-1000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":null},"role":"Data Science","role_family":"Data Science","seniority":"junior","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":13500,"max_usd":32000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":9},"experience_years_min":2,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agile","optional":false},{"name":"Airflow","optional":false},{"name":"Amazon Kinesis","optional":false},{"name":"Amazon Redshift","optional":false},{"name":"Amazon S3","optional":false},{"name":"Apache Hudi","optional":false},{"name":"Apache Iceberg","optional":false},{"name":"Apache Kafka","optional":false},{"name":"AWS","optional":false},{"name":"AWS Step Functions","optional":false},{"name":"CI/CD","optional":false},{"name":"Databricks","optional":false},{"name":"Delta Lake","optional":false},{"name":"ETL/ELT","optional":false},{"name":"Grafana","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false}],"status":"live","first_seen_at":"2026-10-01T00:00:00Z","employer_posted_date":"2026-10-01","last_verified_at":"2026-10-04T01:43:00Z","board_verified":true,"closed_at":null,"days_open":3,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":3},"description":"Department:\nTechnologyOur Company Promise\nWe 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.\nJob Description:\nJob Summary\nWork 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\nResponsibilities\nAssemble large, complex sets of data that meet non-functional and functional business requirements\nIdentify, design and implement internal process improvements including re-designing infrastructure for greater scalability, optimizing data delivery, and automating manual processes\nBuild required infrastructure for optimal extraction, transformation and loading of data from various data sources using AWS and SQL technologies\nBuild analytical tools to utilize the data pipeline, providing actionable insight into key business performance metrics including operational efficiency and customer acquisition\nWork with stakeholders including data, design, product and executive teams and assisting them with data-related technical issues\nWork with stakeholders including the Executive, Product, Data and Design teams to support their data infrastructure needs while assisting with data-related technical issues\nGenerate or adapt equipment and technology to serve user needs\nMay perform other job duties as directed by Employee's Leaders\nAdvanced SQL development, data modelling, performance tuning, and enterprise-scale analytical datasets.\nAdvanced Python development for reusable data frameworks, automation, testing, and production-grade engineering\nDesign and ownership of scalable ETL/ELT architectures, data lake, lakehouse, and enterprise integration patterns.\nAdvanced AWS data engineering experience across Glue, S3, Athena, Redshift, EMR, Kinesis, Step Functions, Airflow/MWAA, security, and reliability.\nData quality, governance, APIs, CI/CD pipelines, observability, automated testing, and production support leadership\nLead scalable enterprise data engineering foundations supporting Agent Observability, Ops Enablement, and future autonomous operations.\nOwn telemetry ingestion, data processing pipelines, evaluation datasets, and reusable data engineering frameworks on AWS.\nServe as the technical partner across Product, AI, Operations, and Engineering teams while improving platform reliability, governance, and scalability.\nKnowledge, Skills and Abilities\nKnowledge 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\nKnowledge of design techniques, tools, and principles involved in production of precision technical plans, blueprints, drawings, and models\nAbility to use logic and reasoning to identify the strengths and weaknesses of alternative solutions, conclusions or approaches to problems\nAbility to understand new information for both current and future problem-solving and decision-making\nSkilled in identifying complex problems and reviewing related information to develop and evaluate options and implement solutions\nAbility to recognize when an issue has occurred or is likely to occur, without needing to diagnose or resolve the problem.\nAbility to combine pieces of information to form general rules or conclusions (includes finding a relationship among seemingly unrelated events)\nAbility to switch efficiently between multiple tasks or information sources, such as spoken instructions, system alerts, or data inputs.\nAbility 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).\nAbility to recognize defined patterns-such as shapes, words, or signals-even when they are embedded within distracting or complex information.\nAdvanced SQL development, data modelling, performance tuning, and enterprise-scale analytical datasets.\nAdvanced Python development for reusable data frameworks, automation, testing, and production-grade engineering\nDesign and ownership of scalable ETL/ELT architectures, data lake, lakehouse, and enterprise integration patterns.\nAdvanced AWS data engineering experience across Glue, S3, Athena, Redshift, EMR, Kinesis, Step Functions, Airflow/MWAA, security, and reliability.\nData quality, governance, APIs, CI/CD pipelines, observability, automated testing, and production support leadership\nDatabricks and Apache Spark\nIceberg, Delta Lake, and Hudi\nKafka, Kinesis, and streaming architectures\nAI/GenAI telemetry, vector databases, RAG analytics, QuickSight, or Grafana\nEducation\nRequired: Bachelor's degree in Computer Science, Engineering, Information Systems or related field and/or equivalent formal training\nExperience\nRequired: Intermediate level experience, fully functioning broad knowledge in:Cloud infrastructure, DataLake\nETL experience ensuring source to target data integrity\nVarious filetypes (Delimited Text, Fixed Width, XML, JSON, Parque).\nServiceBus, setting up ingress and egress within a subscription, or relevant AWS Cloud services administrative experience.\nUnit Testing, Code Quality tools, CI/CD Technologies, Security and Container Technologies\nAgile development experience and Agile ceremonies and practices \n2-5 years of relevant work-related experience\nAdvanced SQL development, data modelling, performance tuning, and enterprise-scale analytical datasets.\nAdvanced Python development for reusable data frameworks, automation, testing, and production-grade engineering\nDesign and ownership of scalable ETL/ELT architectures, data lake, lakehouse, and enterprise integration patterns.\nAdvanced AWS data engineering experience across Glue, S3, Athena, Redshift, EMR, Kinesis, Step Functions, Airflow/MWAA, security, and reliability.\nData quality, governance, APIs, CI/CD pipelines, observability, automated testing, and production support leadership\n\nPreferred Experience\nDatabricks and Apache Spark\nIceberg, Delta Lake, and Hudi\nKafka, Kinesis, and streaming architectures\nAI/GenAI telemetry, vector databases, RAG analytics, QuickSight, or Grafana\nOther Qualifications\nMust meet confidentiality expectations as to confidential, proprietary and sensitive Company information\nAbility to work extended hours as needed\nAbility to work onsite approximately 3 days per week and as required by the business.\nSouthwest Airlines is an Equal Opportunity Employer.\nPlease print/save this job description because it won't be available after you apply.","description_format":"text","description_chars":7012,"description_truncated":false,"requirements":{"experience_years_min":2,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"bachelor","optional":false},"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Artificial Intelligence"],"lifecycle":[{"event":"open","at":"2026-10-02T12:01:20Z"}],"visa":[],"liveness":{"score":86,"band":"hot","label":"Hiring now","p_open":1,"p_active":0.86,"p_room":1,"age_days":2,"expected_fill_days":24,"reasons":["conf:2","win:early","comp:junior"],"computed_at":"2026-10-03T05:45:00Z"},"pay":null,"html_url":"https://alion.io/job/southwest-airlines-data-engineer-ai-analytics","json_url":"https://alion.io/job/southwest-airlines-data-engineer-ai-analytics.json","meta":{"generated_at":"2026-10-04T02:56:18Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","usage":{"tier":"crawler","counted_by":"address","units_charged":1,"used_today":4456,"day_limit":5000,"remaining_today":544,"minute_limit":60,"resets_at":"2026-10-05T00:00:00Z"}}}