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Strong Tier‑1 brand, mid-level generalist data role, Bangalore location, and broad skillset requirements heighten competition.
Core data engineering skills are transferable, but security telemetry and SecOps specialization raise domain specificity.
Explicit 5–8 years plus many mandatory AWS, PySpark, Python, Terraform and security requirements make filters strict.
Lead design, build, and maintenance of scalable data pipelines (batch and real-time) to support AI/ML and security use cases within the Group Security Team.
Set up and own the Group Security Data Platform integrating security telemetry data and other data assets to enable analytics and detection capabilities.
Develop and implement automation frameworks and DevOps practices including CI/CD and infrastructure-as-code for data engineering solutions in AWS environment.
5-8 years experience as a Data Engineer in data-intensive environments.
Proficiency in AWS cloud services including EC2, S3, Lambda, Athena, Kinesis, Kafka, Redshift, Snowflake, Glue, EMR, DynamoDB, IAM, SecretManager, Step functions, SQS, SNS, Cloud Watch.
Strong Python skills with experience in complex framework development; mandatory experience with PySpark/Spark and performance optimization.
Bachelor's or Master's degree in Engineering (Computer Science, IT or relevant field).
Experienced working at medium to complex engineering initiatives with ownership over technical strategy and roadmaps.
Familiar with cloud-based DevSecOps, automation, and security best practices such as encryption (SSL/TLS, data at rest/in transit).
Skilled in integrating data solutions with enterprise security platforms (e.g., ServiceNow SecOps) and collaborating across data science and engineering teams.