Senior Manager, Data Engineering

Company Description

ATPCO is the foundation of flight shopping, providing pricing and retailing data, tools, and services to 500+ airlines, global distribution systems, sales channels, and technology companies. In addition, ATPCO links the entire airline community together, collaborating to develop industry standards for airline distribution and end-to-end technology solutions. As a result, ATPCO solutions work seamlessly across existing, new, and evolving technologies and methods from shopping to settlement. Airline-owned and reliably supporting air travel for more than 55 years, ATPCO is everywhere people buy flights.

We consider qualified applicants for employment without regard to race, gender, age, color, religion, national origin, citizenship status, marital status, disability, sexual orientation, protected military/veteran status, gender identity or expression, genetic information, marital status, medical condition, or any other legally protected factor.

Job Description

Position Summary 

As the Senior Manager of Data Engineering, you will be accountable for delivering impactful data solutions that align with company objectives. This includes strong collaboration with product, and analytics teams, with a focus on data-driven impact and scalability. In this role, you will lead the data engineering team, ensuring seamless execution of data roadmaps and fostering engineering excellence. As a leader of leaders, you will mentor managers, team leads, and architects, empowering them to build high-performing teams dedicated to creating valuable data products. 

What will you do: 

• Work with Product and Analytics teams to define and implement a strategic data roadmap that includes advanced analytics and AI/ML capabilities. Champion data-mesh principles to enable decentralized ownership and accessibility across teams. 

• Design and oversee scalable, robust data architectures and ETL pipelines, leveraging AWS services like Redshift, Glue, and Lambda, ensuring support for machine learning, advanced analytics, and governance. 

• Partner closely with data scientists and analytics teams to create data infrastructures that support real-time analytics and ML model deployment, delivering actionable insights that drive business decisions. 

• Drive initiatives to enhance data security, stability, and governance, establishing frameworks that uphold quality, consistency, and regulatory compliance across ATPCO’s data ecosystem. 

• Mentor and lead multiple teams of data engineers and analytics professionals, fostering technical growth and a shared commitment to data quality. Encourage innovative approaches to data automation and performance tuning. 

• Continuously refine data engineering practices for efficiency and resilience, optimizing workflows and monitoring costs within the AWS environment, with a focus on scalable, automated data solutions. 

• Foster a culture that values innovation and experimentation, empowering teams to explore new techniques in data, analytics, and AI, including generative AI models. 

• Ensure the operational health and performance of data products in cloud environments, maintaining high availability, fault tolerance, and performance optimization across all services. 

• Establish a data lake, data mesh, and advanced data modeling-first approach, creating well-structured data practices with an API-driven methodology that improves usability and governance. 

• Own and lead internal data analytics platforms, collaborating with finance and operations to identify cost optimization opportunities, manage data product P&L, and establish benchmarks for data-driven outcomes. 

What will make you a great fit: 

• 7+ years of experience in data engineering roles focused on high-volume, complex data applications, with 5+ years in people leadership. 

• Proven ability to build and manage high-quality data products and infrastructure, with experience leading cross-functional teams in complex data environments. 

• Technical expertise in a wide range of AWS services, including Redshift, Glue, S3, Lambda, EMR, Kinesis, EC2, API Gateway, serverless technologies, and container services such as ECS and EKS, integrated with data orchestration tools. Proficiency in Python, SQL, or Scala, plus experience with ML frameworks. 

• Experience with database management (RDBMS, NoSQL, graph databases) and big data frameworks, including Apache Spark and Hadoop, showcasing your ability to design and optimize complex data architectures and process large-scale data efficiently. 

• Strong communication skills to align cross-functional teams