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Job Description
Structured overview of role & requirementsAbout This Role
Architect, design, and develop large-scale cloud-native data platforms using Databricks, Spark, PySpark, Python, and AWS.
Build high-performance distributed data processing solutions for massive-scale datasets, including batch and real-time processing.
Lead architectural decisions and establish engineering standards while mentoring engineers and providing technical guidance.
Minimum Requirements
10–14 years of software/data engineering experience with strong hands-on expertise.
Proficiency in Databricks, Python, PySpark, Apache Spark.
Experience with AWS ecosystem services including S3, Glue, Redshift, EMR, Athena, Lambda, or EventBridge.
Experience with Data Lakes, Delta Lake, Data Warehousing, streaming technologies (Kafka/Kinesis/SQS/RabbitMQ), and DevOps tools like Terraform/Ansible and CI/CD.
Ideal Candidate Profile
Senior individual contributor comfortable balancing hands-on engineering and architecture leadership.
Experienced in designing scalable, distributed data platforms working at cloud scale with large datasets.
Capable of influencing technical direction, driving engineering standards, and collaborating across global teams.