Summary
Overview
Work History
Education
Skills
Certification
Timeline
Languages
Projects
AdministrativeAssistant
Aditya Prakash Singh

Aditya Prakash Singh

Ghazipur

Summary

Results-driven DevOps/MLOps/Data Engineer with expertise in Python, SQL, Spark, Docker, Kubernetes, Terraform, Airflow, and MLflow, delivering scalable, secure, and automated cloud-native systems. Experienced in building enterprise-grade ETL pipelines, CI/CD workflows, and ML model deployments, while aligning with SaaS business models. Committed to business-focused engineering, agile execution, and high-quality outcomes.

Overview

3
3
years of professional experience
5
5
Certificate

Work History

Software Developer

Amdocs Development Pvt. Ltd.
Pune
09.2022 - Current

Project - Three UK.

Developed and automated CI/CD pipelines using GitLab and Jenkins, implementing secure code reviews, automated testing, and release gates to achieve zero-downtime deployments.

Containerized and orchestrated microservices using Docker and Kubernetes, delivering scalable, resilient systems across hybrid cloud environments.

Deployed and managed cloud infrastructure as code (IaC)with Terraform and Ansible, ensuring repeatable, auditable infrastructure provisioning.

Built and optimized data models and dashboards using QuickSight and Power BI, enabling business stakeholders to access actionable product analytics.

Project - Tef Chile.

Collaborated with data scientists and ML engineers to productionize machine learning models using Airflow, MLFlow, and ONNX pipelines, supporting inferencing at scale.

Enhanced data pipeline monitoring, logging, and observability, improving SLA compliance and troubleshooting efficiency.

Participated in Agile ceremonies, delivered continuous improvements, and mentored junior team members on coding best practices, secure development, and DevOps automation.

Graduate Engineer Trainee

British Telecom
Gurgaon
01.2022 - 07.2022

Project - Unilever

Implemented automation scripts in Python and Bash to streamline network security, VPN access, and firewall rule configurations, reducing manual interventions.

Monitored and troubleshot infrastructure and systems in Linux environments, solving performance bottlenecks and escalating fewer tickets.

Supported product analytics and log monitoring for system health and access controls, improving visibility and compliance.

Collaborated with cross-functional teams to analyze requirements and deliver solutions that met security and performance standards.

Documented processes and assisted in developing automated toolchains, laying the foundation for continuous integration and robust DevOps practices.

Education

Bachelor of Engineering - Computer Science Engineering

Chandigarh University
Chandigarh
07.2022

Skills

Programming: Python, SQL, Java, Golang, Shell, C

Cloud: AWS, Azure, GCP, Snowflake, Databricks

DevOps/MLOps: GitLab CI/CD, Jenkins, Docker, Kubernetes, Terraform, Ansible, Airflow, MLflow

Data engineering: ETL/ELT, Spark, PySpark, data modeling, data quality, product analytics

LLM/NLP: Prompt engineering, LangChain, RAG workflows, ONNX pipelines

Systems: distributed systems, microservices, event-driven architectures

Tools: Git, Jira, Power BI, QuickSight

Soft skills: agile, collaboration, business-focused delivery, documentation

Certification

  • Building Modern Python Applications on AWS (Coursera)
  • Managing Big Data with MySQL (Coursera)
  • Industrial IoT on Google Cloud (Coursera)
  • Introduction to Data Science in Python (Coursera)
  • R Programming (Coursera)

Timeline

Software Developer

Amdocs Development Pvt. Ltd.
09.2022 - Current

Graduate Engineer Trainee

British Telecom
01.2022 - 07.2022

Bachelor of Engineering - Computer Science Engineering

Chandigarh University

Languages

Hindi
First Language
English
Advanced (C1)
C1

Projects

Cloud ETL pipeline: designed scalable ETL pipelines using PySpark, AWS Glue, and Redshift for high-volume data processing

CI/CD automation: built automated CI/CD pipelines with GitLab, Jenkins, Docker, and Kubernetes, reducing release cycles

ML model deployment: Deployed ML models using Airflow, MLFlow, and ONNX for scalable inferencing, aligned with business needs

Infrastructure automation: used Terraform and Ansible for IaC, ensuring secure, repeatable cloud resource provisioning

Analytics dashboards: Developed Power BI and QuickSight dashboards to monitor pipeline SLAs and business KPIs for stakeholders

Aditya Prakash Singh