Tech Lead Data Engineer Global - Redshift

swa; India; On-site; INR 3,000,000 - 6,000,000; Full time

Job summary

Southwest Airlines seeks a Tech Lead Data Engineer - Redshift to steer enterprise data platform initiatives, driving architecture, automation, and scalable data solutions for analytics and AI. You will mentor engineers, set technical direction, and partner with product, data, and engineering teams across the company.

Ideal candidates bring deep AWS/Redshift expertise, SQL skills, and hands-on leadership to deliver reliable, cost-efficient data capabilities at scale for enterprise decision making.

Qualifications

• Strong engineering fundamentals in data systems and analytics.
• Experience with scalable data architectures and data modeling.
• Proficiency in designing robust data pipelines and ETL processes.
• Ability to mentor engineers and guide complex data solutions.
• Familiarity with DevOps practices and modern cloud tooling.

Responsibilities

• Lead the big data platform design and delivery.
• Build and automate ingestion, enrichment, and analytics pipelines.
• Architect scalable, secure data workflows across teams.
• Improve data delivery, performance, and cost efficiency.
• Mentor engineers and collaborate with product and design teams.
• Optimize data solutions for high-volume enterprise analytics.

Skills

Big data

AWS

Redshift

SQL

Data pipelines

Technical leadership

DevOps

Tools

Redshift

AWS

Job 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:

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

As a Tech Lead Data Engineer - Redshift, you'll provide technical leadership for the enterprise data platform that powers analytics, machine learning, AI, and critical business decision-making across Southwest. You'll join the Redshift Pod, which is responsible for delivering scalable, secure, and reusable data capabilities that make trusted enterprise data available across the Company. In this role, you'll set the technical direction for the Redshift platform, driving architecture, automation, performance optimization, and operational excellence while mentoring Engineers and guiding complex data solutions from design through deployment. Leveraging deep expertise in AWS, Redshift, SQL, infrastructure automation, and modern DevOps practices, you'll help enhance platform reliability, scalability, security, and cost efficiency while enabling high-volume data processing and analytics at enterprise scale. By partnering with Product, Data, and Engineering Teams across Southwest, you'll play a key role in advancing the Company's data-driven strategy while creating opportunities for innovation, continuous improvement, and professional growth within a high-performing Global Engineering Team.

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 ac