Data Architect / Analytics Engineer
We are seeking an experienced Data Architect / Analytics Engineer to design and implement a Medallion Architecture (Bronze / Silver / Gold) to support analytics, machine learning, and data science workloads.
This role focuses on data orchestration, data quality, and analytical modeling, ensuring raw data is transformed into trusted, AI-ready datasets that can be reliably consumed by data scientists, analysts, and downstream applications.
Scope of Services
Medallion Architecture Design
Design and implement Bronze, Silver, and Gold layers
Define data standards, naming conventions, and storage patterns
Establish clear lineage from raw ingestion to curated analytics datasets
Data Orchestration & Pipelines
Build and manage orchestrated data pipelines for batch and near-real-time processing
Implement dependency management, retries, and failure handling
Schedule and monitor workflows to ensure data freshness and reliability
Data Modeling for Analytics & AI
Design analytical and feature-ready datasets for BI, ML, and data science
Create denormalized and performance-optimized data models
Support feature engineering and reuse across ML workflows
Data Quality & Governance
Implement data validation, completeness, and freshness checks
Define SLAs and monitoring for critical datasets
Support auditability, reproducibility, and versioning
AI & Data Science Enablement
Partner with data scientists to understand model input needs
Ensure datasets are consistent, explainable, and reusable
Support experimentation and production ML pipelines
Optimization & Improvement
Identify opportunities to improve pipeline performance and cost
Refine data structures as business and modeling needs evolve
Required Experience
Strong experience designing Medallion Architecture (Bronze/Silver/Gold)
Hands-on experience with data orchestration and pipeline design
Strong SQL skills and experience with analytical data modeling
Experience supporting AI / ML / data science workflows
Solid understanding of data warehousing and lakehouse concepts
Strong problem-solving and communication skills
Nice to Have
Experience with cloud data platforms (AWS, Azure, or GCP)
Experience with orchestration tools (Airflow, n8n, Prefect, Dagster, etc.)
Familiarity with feature stores or ML lifecycle tooling
Experience with data quality frameworks or observability tools
Apply Now
Apply Now
This role focuses on data orchestration, data quality, and analytical modeling, ensuring raw data is transformed into trusted, AI-ready datasets that can be reliably consumed by data scientists, analysts, and downstream applications.
Scope of Services
Medallion Architecture Design
Design and implement Bronze, Silver, and Gold layers
Define data standards, naming conventions, and storage patterns
Establish clear lineage from raw ingestion to curated analytics datasets
Data Orchestration & Pipelines
Build and manage orchestrated data pipelines for batch and near-real-time processing
Implement dependency management, retries, and failure handling
Schedule and monitor workflows to ensure data freshness and reliability
Data Modeling for Analytics & AI
Design analytical and feature-ready datasets for BI, ML, and data science
Create denormalized and performance-optimized data models
Support feature engineering and reuse across ML workflows
Data Quality & Governance
Implement data validation, completeness, and freshness checks
Define SLAs and monitoring for critical datasets
Support auditability, reproducibility, and versioning
AI & Data Science Enablement
Partner with data scientists to understand model input needs
Ensure datasets are consistent, explainable, and reusable
Support experimentation and production ML pipelines
Optimization & Improvement
Identify opportunities to improve pipeline performance and cost
Refine data structures as business and modeling needs evolve
Required Experience
Strong experience designing Medallion Architecture (Bronze/Silver/Gold)
Hands-on experience with data orchestration and pipeline design
Strong SQL skills and experience with analytical data modeling
Experience supporting AI / ML / data science workflows
Solid understanding of data warehousing and lakehouse concepts
Strong problem-solving and communication skills
Nice to Have
Experience with cloud data platforms (AWS, Azure, or GCP)
Experience with orchestration tools (Airflow, n8n, Prefect, Dagster, etc.)
Familiarity with feature stores or ML lifecycle tooling
Experience with data quality frameworks or observability tools
Apply Now
Apply Now