About Mani Deepak
English
Native or bilingual
Dutch
Conversational
French
Basic
Experience
- NikeData/DevOps EngineerSeptember 2020 - Today (5 years and 9 months)Architected and implemented scalable infrastructure on AWS following the Well-Architected Framework, developed reliable data pipelines. Built and maintained automated CI/CD pipelines for development and deployment lifecycle. Key responsibilities:• • Built reproducible analytics pipelines (Databricks/Jobs, Airflow) by following standards like Unit testing, maintaining code quality checks and thereby producing reliable code.• • Designed CI/CD: automated training, testing, packaging and release pipelines using Jenkins• • Creation of infrastructure using IaC approach using Terraform• • Containerized applications (Docker); created Helm charts and deployed apps to Kubernetes (EKS)• • Established observability: metrics, latency, throughput monitoring and alerting (Prometheus, SignalFX, Splunk).• • Maintained Kubernetes clusters, tuned CI/CD for workloads, and implemented infrastructure as code (Terraform) for reproducible environments. Technologies: Snowflake, Databricks, MLflow, AWS (EKS, EC2, S3, IAM, Secrets Manager), Terraform, Kubernetes, Helm, Seldon/KFServing, Databricks Jobs, Airflow, Jenkins, GitHub Actions, Docker, Python, Shell scripting, Prometheus, SignalFX, Splunk, ELK
- Pharma Client in Germany (Accenture)Data Engineer/Cloud Architect/DevOps EngineerMay 2019 - April 2020 (11 months)Designed and implemented AWS infrastructure and platform tooling to support web and real-time streaming applications, improving reliability and deployment repeatability.
- Insurance client in Belgium (Accenture)Big Data Engineer/DevOps EngineerNovember 2017 - May 2019 (1 year and 6 months)Engineered real-time data ingestion and NoSQL storage for insurance systems to enable timely analytics and search over high-volume data.• • Developed CI/CD pipelines to automate build, test and deployment (Jenkins).• • Designed NoSQL data models and ingestion pipelines using Kafka and Spark (Scala) to preserve data integrity and support real-time access in HBase.• • Enabled search capabilities over ingested data with Solr and Lily to improve data discoverability and query performance.• • Led cloud POCs for Hadoop and implemented CI/CD for Hadoop applications using Jenkins and JFrog Artifactory. Technologies: Hadoop (Cloudera), HBase, Spark, Scala, Solr, Lily, AWS CloudFormation, Kafka, Kafka Connect, Git, Jenkins
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Education
- AWS Certified Big Data - SpecialtyAmazon Web Services (AWS)AWS Certified Big Data - Specialty
- AWS Certified Solutions Architect AssociateAmazon Web Services (AWS)AWS Certified Solutions Architect Associate