Sr Data Engineer – AI Ops at Southwest Airlines

, , India -

Full Time

Start Date

Immediate

Expiry Date

15 Aug, 26

Salary

0.0

Posted On

17 May, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

AWS, Python, SQL, Snowflake, Airflow, ETL, CI/CD, Data Pipeline Design, Data Observability, Infrastructure as Code, Agile, Data Lake, Spark, Databricks, Kinesis, S3

Industry

Airlines and Aviation

Description

Department: Technology Our 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: As a Sr Data Engineer Global supporting Southwest’s AI Platform Operations, you’ll build and operate the data pipelines that power production AI workloads at scale. This role focuses on solving complex data challenges by designing reliable, observable, and scalable data infrastructure using modern AWS data services and cloud‑native practices. You’ll own pipeline performance and data quality end‑to‑end—monitoring, troubleshooting, and tuning systems while implementing retraining pipelines and data‑quality checks that keep AI models and agentic systems performing as data evolves. Beyond day‑to‑day operations, you’ll lead meaningful platform enhancements by redesigning infrastructure for scalability, improving lineage and observability, and automating manual processes. Working closely with Data, Product, Engineering, and Executive Stakeholders, you’ll apply strong judgment and technical expertise to deliver trusted data foundations that enable Southwest’s AI platforms to deliver consistent, high‑value outcomes across the Company. 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, 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 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. Education Required: Bachelor's degree in Computer Science, Engineering, Information Systems or related field and/or equivalent formal training Experience Required: Advanced level experience, seasoned and specialized knowledge in Cloud infrastructure, DataLake 5-7 years of relevant work-related experience 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+ years of experience with production data engineering—pipelines, warehousing, observability 4+ years of experience with Snowflake/Redshift/BigQuery + Airflow/Glue/dbt in production 2+ years of experience with data quality, lineage, observability tooling (Monte Carlo, Great Expectations, OpenLineage) 3+ years of experience with AWS data services—Glue, EMR, Kinesis, S3, Athena 3+ years of experience in Python for data ops; CI/CD and IaC for data pipelines Preferred experience in: Data contracts, schema registry, governance tooling Spark/Databricks experience for batch retraining workloads Lakehouse formats (Iceberg, Delta, Hudi) Experience supporting ML/AI feature stores, model registries, or vector DBs Streaming systems—Kafka, Kinesis—at scale Other Qualifications Must meet confidentiality expectations as to confidential, proprietary and sensitive Company information Ability to work extended hours as needed Southwest Airlines is an Equal Opportunity Employer. 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Responsibilities

Build and operate scalable data pipelines to power production AI workloads and agentic systems. Lead platform enhancements by improving observability, automating manual processes, and redesigning infrastructure for scalability.