Services
Expert Solutions for Your Data & Cloud Needs
From architecting data pipelines to optimizing cloud infrastructure and deploying ML systems, HDS Consulting provides the technical expertise needed to turn your data challenges into competitive advantages.
Our expertise spans three core areas that work together to create comprehensive technical solutions: Data, Cloud and ML.
Data
Engineering robust data pipelines and platforms that transform raw data into actionable insights, enabling data-driven decision making at scale.
Cloud
Architecting scalable, secure cloud infrastructure that enables rapid innovation while optimizing costs and maintaining reliability.
ML(Ops)
Building production-ready machine learning pipelines and infrastructure that bridge the gap between experimentation and real-world impact.
Data Engineering Services
Comprehensive data engineering solutions from pipeline development to platform architecture.
Data Pipeline Development
Build scalable ETL/ELT workflows using Apache Airflow, dbt, Spark, and modern data stack tools.
Data Platform Architecture
Design end-to-end data solutions on cloud platforms (AWS, Azure, GCP) with data warehouses, lakes, and lakehouses.
Data Quality & Testing
Implement data validation frameworks, monitoring systems, and automated testing for reliable data.
Real-time Data Streaming
Build streaming data pipelines using Kafka, Kinesis, or Pub/Sub for real-time analytics and event processing.
Cloud Engineering Services
Expert cloud infrastructure and DevOps services for modern, scalable applications.
Infrastructure as Code
Automate infrastructure provisioning and management using Terraform, CloudFormation, or CDK.
Cloud Architecture Design
Design resilient, scalable cloud architectures leveraging serverless, containers, and managed services.
DevOps & CI/CD
Implement automated deployment pipelines, GitOps workflows, and continuous integration best practices.
Cloud Migration & Optimization
Migrate workloads to the cloud and optimize existing infrastructure for cost and performance.
ML Engineering Services
Production-ready MLOps solutions that bring machine learning models from lab to production.
MLOps Pipeline Setup
Design and implement end-to-end ML pipelines for training, validation, and deployment automation.
Model Deployment & Serving
Deploy ML models to production using containers, serverless, or managed ML platforms with proper scaling.
ML Monitoring & Observability
Implement monitoring for model performance, data drift, feature drift, and prediction quality.
ML Infrastructure
Build scalable infrastructure for feature stores, model registries, and experiment tracking using e.g. MLflow and cloud services.
Flexible Engagement Models
Choose the collaboration model that works best for your organization
Fixed-scope engagements with clear deliverables and timelines for specific initiatives or proof-of-concepts.
Join your team full-time or part-time to provide hands-on technical leadership and execution.
Strategic guidance on technical architecture, tool selection, and roadmap planning without full implementation.