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:
About Us
At Southwest Airlines, we believe that flying should feel like freedom. For over 50 years, we’ve been connecting people to what matters most with low fares, legendary hospitality, and a heart for service. Our culture is built on the principles of fun, friendliness, and family, making us one of the most admired workplaces in the world.
If you’re passionate about making a difference, love working in a fast-paced environment, and want to help millions of travelers reach their destinations with a smile, Southwest Airlines is the place for you. Here, your career can truly take flight.
Job Summary
- The Data Lake 2.0 Pod owns and builds the common patterns and frameworks Southwest uses to collect, store, and expose data across the enterprise using modern cloud architectures. The team operates with a DevOps mindset and Agile principles — providing reusable Infrastructure-as-Code building blocks that hundreds of Southwest application teams consume and own within their own AWS environments to power analytics, ML, and AI.
- As Tech Lead Data Engineer – Data Lake 2.0, you'll set the technical direction for the platform — designing scalable, secure, and reusable capabilities that engineering teams across the enterprise depend on. You'll lead hands-on development of AWS services and platform automation, drive engineering excellence through standardization and reusable patterns, and mentor a growing team in our Hyderabad office as it takes ownership of one of Southwest's most consequential data platforms.
- Responsible for one or more project teams of other data engineers for all stages of design and development for complex, secure and performant data solutions and models, including design, analysis, coding, testing, and integration of structured/unstructured data. Work with “product” team to design and develop a scalable data processing infrastructure. Apply an Agile approach to data science and work closely with our team of analysts, technical product owners, and data scientists to drive real business value.
Responsibilities
- Lead and develop the big data platform
- Design, build, implement, document and automate ingestion (real time and batch), enrichment and analytics data pipelines using big data tools and technologies
- 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
- Implement Big Data Solutions as a hands-on Technical Lead
- Process & ingest high volumes of data & transactions with full Life Cycle Implementation(s) of Scalable Big Data & Data Lake solutions
- 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 engage in active, focused listening—accurately interpreting technical information, validating understanding through targeted questions, and maintaining appropriate communication flow.
- 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:
- AWS core services and networking/security fundamentals — S3, Lake Formation, Glue, Athena, Redshift Spectrum, IAM
- IaC using Terraform or CloudFormation with reusable, multi-environment patterns
- Hands-on technical contribution — this Tech Lead role builds alongside setting direction
- Platform-as-a-product design where application teams consume and own their AWS environments
- Data ingestion patterns — S3 replication, AWS File Transfer, event-driven architectures
- Observability and operational excellence for data platforms (CloudWatch, logging, tracing)
- SRE mindset for a data platform — reliability, error budgets, cost efficiency
- Technical mentorship and coaching for engineers
Education
- Required: Bachelor's degree in Computer Science, Engineering, Information Systems or related field and/or equivalent formal training
Experience
- Required: Expert level experience, expansive and far reaching knowledge in:
- Building and optimizing data sets, ‘big data’ data pipelines and architectures
- Performing root cause analysis on external and internal processes and data to identify opportunities for improvement and answer questions
- Excellent analytic skills associated with working on unstructured datasets
- Building processes that support data transformation, workload management, data structures, dependency and metadata
- 8-10 years of relevant work-related experience
- Preferred:
- End-to-end technical direction for an enterprise data lake or comparable data platform
- Hands-on AWS data platform development at enterprise scale
- Databricks or comparable lakehouse platform experience
- Lakehouse formats — Iceberg, Delta Lake, or Hudi
- Platforms serving analytics, ML, and AI workloads
- FinOps and cost optimization across AWS data services
- Data governance, semantic layer, metadata management, or business glossary
- Coaching engineers across a globally distributed team
- Cross-functional partnership with peer Tech Leads across Technology
- Technical leadership within a large enterprise data ecosystem
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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