Build and manage data infrastructure on
AWS
, including S3, Glue, Lambda, Open Search, Athena, and CloudWatch using IaaC tool like Terraform
Design and implement scalable
ETL pipelines
with integrated validation and monitoring.
Set up
data quality frameworks
using tools like
Great Expectations
, integrated with PostgreSQL or AWS Glue jobs.
Implement
automated validation checks
at key points in the data flow: post-ingest, post-transform, and pre-load.
Build centralized logging and alerting pipelines (e.g., using CloudWatch Logs, Fluent bit ,SNS, File bit ,Logstash , or third-party tools).
Define CI/CD processes for deploying and testing data pipelines (e.g., using Jenkins, GitHub Actions)
Collaborate with developers and data engineers to enforce schema versioning, rollback strategies, and data contract enforcement.

Preferred candidate profile

5+ years of experience in DataOps, DevOps, or data infrastructure roles.
Proven experience with infrastructure-as-code (e.g., Terraform, CloudFormation).
Proven experience with real-time data streaming platforms (e.g., Kinesis, Kafka).
Proven experience building production-grade data pipelines and monitoring systems in
AWS
.
Hands-on experience with tools like
AWS Glue
,
S3
,
Lambda
,
Athena
, and
CloudWatch
.
Strong knowledge of
Python
and scripting for automation and orchestration.
Familiarity with
data validation frameworks
such as Great Expectations, Deequ, or dbt tests.
Experience with SQL-based data systems (e.g., PostgreSQL).
Understanding of security, IAM, and compliance best practices in cloud data environments.

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