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Tier-1 brand, metro location, and generalist senior data role increases applicant competition.
Core data engineering skills like Python, Spark, and AWS are easily transferable across industries.
Explicit 8–10 years plus mandatory Python/Spark/AWS and data engineering skills enforce strict filtering.
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Design, implement, and maintain software and web applications with focus on Data Engineering using technologies like Python, PySpark, REST APIs, and AWS.
Collaborate with cross-functional teams to translate business requirements into scalable and efficient software architecture and solutions.
Lead or mentor team members, oversee development documentation, track application performance metrics, and incorporate automation and Test-Driven Development (TDD).
8–10 years of software design and development experience with a focus on Data Engineering.
Proficient in Python, Apache Spark, SQL, and AWS infrastructure (S3, Lambda, EC2, EKS, CloudWatch, Kinesis/Kafka, SNS, SQS).
Experience with REST APIs, Docker, Kubernetes, and CI/CD tools such as Git and Jenkins.
Bachelor's Degree preferred; combination of coursework and experience may be considered.
Technical leadership with strong communication and ability to collaborate across functions in complex environments.
Experienced in building scalable ETL and data engineering systems, including batch and stream processing, data lakes, and cloud-native architectures.
Proactive in adopting new technologies such as Kubernetes, Databricks, and Graph Databases to optimize applications and processes.