Back
Mid-level data engineer in Bangalore with broad cloud and data stack attracts high applicant density.
Core data engineering skills transfer across industries, but security-focused requirements increase domain specificity.
Explicit 5–8 years requirement plus many mandatory technologies increases filtering rigor.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Own and develop the Group Security Data Platform to ingest and process security telemetry and related data for AI/ML and security analytics.
Design, build, and maintain scalable batch and real-time data pipelines using AWS services to support security use cases and data products.
Lead end-to-end data engineering lifecycle including requirement gathering, data modeling, development, testing, deployment (DevSecOps), and data security implementation.
5-8 years of experience as a Data Engineer in data-intensive environments.
Proficiency in AWS cloud services including EC2, S3, Lambda, Athena, Kinesis, Redshift, Glue, EMR, DynamoDB, IAM, SecretManager, Step Functions, SQS, SNS, CloudWatch.
Strong Python programming skills with experience developing complex frameworks; mandatory knowledge of PySpark/Spark and big data processing.
Bachelor's or Master's degree in Engineering (Computer Science, IT, or relevant field).
Experience owning and leading complex data engineering projects end-to-end with a focus on security telemetry data and AI/ML integration.
Strong expertise in cloud native data engineering on AWS with automation and DevSecOps practices including Terraform, Jenkins, Docker, Kubernetes.
Demonstrated ability to implement data security best practices including encryption in transit and at rest, with proficiency in streaming data processing and event-driven architectures.
