Tech Lead Data Engineer Global - Redshift

About Us

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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

• 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 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.

• Required: Bachelor's degree in Computer Science, Engineering, Information Systems or related field and/or equivalent formal training

• 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
  • Amazon Redshift; distribution keys; sort keys; encoding; WLM; concurrency scaling; data sharing; SQL; Python; Shell scripting; IAM; KMS; VPC; CI/CD; Terraform; CloudWatch; Redshift system tables; backup / disaster recovery; FinOps
• Preferred:

  • AI-assisted development; AWS Glue; Lake Formation; Athena; Amazon S3; Step Functions; AWS Lakehouse; Databricks; AWS certifications

• Must meet confidentiality expectations as to confidential, proprietary and sensitive Company information
• Ability to work extended hours as needed