Data Technology Performance Engineer

3 days ago

Bangalore, India Delta Air Lines Full time

About Delta Tech Hub: S. global airline leader in safety, innovation, reliability and customer experience. 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. 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. Provide technical support and guidance on data-related issues or projects. Leverage cloud-based solutions and frameworks (e.g., AWS) to streamline processes and enhance automation. 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. 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. 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.,) 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.

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