Data Engineer [T500-19944]

About Delta Tech Hub:

Delta Air Lines (NYSE: DAL) is the U.S. global airline leader in safety, innovation, reliability and customer experience. Powered by our employees around the world, Delta has for a decade led the airline industry in operational excellence while maintaining our reputation for award-winning customer service. With our mission of connecting the people and cultures of the globe, Delta strives to foster understanding across a diverse world and serve as a force for social good. Delta has fast emerged as a customer-oriented, innovation-led, technology-driven business. The Delta Technology Hub will contribute directly to these objectives. It will sustain our long-term aspirations of delivering niche, IP-intensive, high-value, and innovative solutions. It supports various teams and functions across Delta and is an integral part of our transformation agenda, working seamlessly with a global team to create memorable experiences for customers.

Responsibilities:

Data Pipeline Development and Maintenance:

• Build and optimize scalable ETL/ELT pipelines to ingest data from diverse sources such as APIs, cloud platforms, and databases.
• Ensure pipelines are robust, efficient, and capable of handling large volumes of data.

Data Integration and Harmonization:

• Implement data transformation and enrichment processes to support analytics and reporting needs.

Data Quality and Monitoring:

• Troubleshoot and resolve issues related to data quality, latency, or performance.

Collaboration with Stakeholders:

• Provide technical support and guidance on data-related issues or projects.

Tooling and Automation:

• Leverage cloud-based solutions and frameworks (e.g., AWS) to streamline processes and enhance automation.
• Maintain and optimize existing workflows while continuously identifying opportunities for improvement.

Documentation and Best Practices:

• Document pipeline architecture, data workflows, and processes for both technical and non-technical audiences.
• Follow industry best practices for version control, security, and data governance.

Continuous Learning and Innovation:

• Stay current with industry trends, tools, and technologies in data engineering and marketing analytics.
• Recommend and implement innovative solutions to improve the scalability and efficiency of data systems.

What you need to succeed (minimum qualifications):

• Bachelor of Science degree in Computer Science or equivalent
• At least 3+ years of experience as a data engineer developing and maintaining data pipelines
• Strong experience with databases and data platforms (AWS preferred)
• Proficiency in Python, SQL, PySpark
• Experience in Data Quality, Data Modeling, Data Analytics/BI, Data Enrichment.
• Understanding of concepts such as normalization, SCD (Slowly changing dimensions) and CDC (Change data capture)
• Experience in working on streaming event platforms such as Kafka/Kinesis
• Knowledge of non-relational databases
• Preferable experience in DBT for data transformation and modeling.
• Good understanding of data warehouses, ETL/ELT, AWS architecture (using Glue, SQS, SNS, S3, step functions etc.,)
• Understanding of orchestration tools such as Airflow
• Ability to create clean, well-designed code and systems
• Strong attention to detail and a commitment to data accuracy.
• Proven ability to learn new data models quickly and apply them effectively in a fast-paced environment.
• Ability to work collaboratively in a team environment.