Data Architect / Analytics Engineer

🌍 Remote, USA 🎯 Full-time 🕐 Posted Recently

Job Description

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

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