Avinash Anad

About Avinash Anad

I’m a Senior Data & Platform Engineer with 13+ years of experience designing, building, and operating cloud-native data platforms at scale.My work focuses on Azure-based data ecosystems, including Airflow orchestration on AKS, Databricks, and metadata-driven pipelines supporting multi-country, enterprise workloads. I care deeply about reliability, cost efficiency, and operational simplicity in production systems.Over the years, I’ve helped teams move from tightly coupled ETL systems to modular, scalable platforms with strong automation, observability, and governance. I’ve worked closely with data scientists, product teams, and business stakeholders to deliver dependable analytics and MLOps pipelines.Core strengths:• Data platform architecture on Azure• Airflow on Kubernetes (AKS) for large-scale, multi-team orchestration• Databricks, Delta Lake, and metadata-driven pipelines• MLOps, automation, and production readiness• Cost optimization and operational resilienceI enjoy working on complex data platforms and cloud-native systems, with a strong focus on reliability, scalability, and operational excellence. My work aligns best with organizations building long-lived platforms that require careful design, collaboration, and steady engineering discipline at scale.

Experience

1. Lead Engineer

   Happiest Minds Technologies

   May 2024 — Present · Bengaluru, IN

   DataOps, DevOps, MLOps:Containerize ML workflows using Docker, with deployment via GitHub Actions and JFrog Artifactory.Use Terraform to provision and manage cloud infrastructure, especially for Azure and OCI deployments.Optimize Helm-based deployments and Kubernetes workload scheduling in Azure Kubernetes Service (AKS).Integrate Azure Key Vault and Service Principals for secure secret management and access control.Build dynamic, parallel pod Airflow DAGs that read configs from Azure Blob and spin KubernetesPodOperator tasks.Implement role-based access control (RBAC) and secret retrieval within containers.Package ML models with support for training, inference, drift detection, and explainability.Automate Python package builds and CI/CD pipelines for JFrog using GitHub Actions.Track GitHub repository KPIs like LOC, PR count, and contributor metrics through automation.Work primarily in Python, SQL, and Bash; skilled with Docker, Terraform, Helm.Design and implement end-to-end data pipelines using Azure Cloud Services, Airflow, Github, and Databricks Unity Catalog.

Education

• Sheridan College

  Postgraduate Degree, Internet of Things and Machine Intelligence

• Visvesvaraya Technological University

  Bachelor of Engineering (BE), Electrical, Electronics and Communications Engineering

  2007 — 2010

• K L E S Polytechnic

  Diploma, Electronics and Communications

  2004 — 2007

Skills

• Microcontrollers
• Data Structures
• Sql
• Linux
• R
• C#
• .net
• Microsoft Sql Server
• Data Analysis
• C
• C++
• Verilog
• Performance Tuning
• Oracle