Data Architect

🚀 Principal Data Architect (Big Data | Cloud | AI/ML) | Remote | High RatesWe're hiring an expert-level Principal Data Architect to design and optimise large-scale, enterprise-grade data solutions. If you have deep hands-on experience withDatabricks, PySpark, and Cloud (Azure/AWS), this role is for you.💰 High rates for top-tier talent🌍 Remote-first - Work from the UK or US🚀 Cutting-edge tech - Databricks, AI/ML, real-time analyticsâš¡ Influence & leadership - Work directly with C-suite & engineering teamsWhat You'll Do:✔ Architect big data solutions for AI/ML-driven analytics & real-time processing✔ Build scalable ETL pipelines using Databricks, PySpark & Delta Lake✔ Design data lakes, warehouses & feature stores on Azure or AWS✔ Implement IAM, DevSecOps & enterprise data governance✔ Mentor teams & drivebest practices for performance, scalability & automationWhat We're Looking For:✔ 5+ years hands-on in Databricks & PySpark (DAGs, transformations, tuning)✔ 5+ years in Cloud (Azure/AWS) - data lakes, warehouses, security✔ Advanced ETL & Data Pipeline Development✔ AI/ML Engineering - MLFlow, Feature Stores, model evaluation✔ Enterprise Consulting & Leadership - Work with C-suite & engineering teamsPreferred (Nice-to-Have):✔ Databricks Certification - Data Engineer / ML Associate✔ Streaming Architectures - Kafka, Spark Streaming✔ Strong SQL & Data Warehousing - Snowflake, Redshift, Synapse⚠️ Hiring Process:To ensure we selectonly the best, our process includes:1️⃣ Short Screening Call - 15 mins to confirm expertise2️⃣ Technical Assessment - Real-world big data challenge📩Ready to work on cutting-edge data projects? Apply now.Minimum Prerequisites PLEASE only apply if you can meet these requirements:1️⃣ Hands-On Expertise in Databricks & PySpark (5+ Years)✔ Strong understanding of Spark architecture, DAGs, and transformations (narrow vs wide)✔ Deep experience with PySpark SQL, DataFrames, and performance tuning✔ Familiarity with Delta Lake, Adaptive Query Execution (AQE), and MLFlow2️⃣ Cloud Data Engineering Mastery (5+ Years in Azure or AWS)✔ Experience with data lakes, warehouses, feature stores, and modern cloud-native architectures✔ Strong knowledge of IAM, security policies, and DevSecOps best practices✔ Hands-on experience with job scheduling, orchestration tools (e.g., Airflow, Databricks Workflows)3️⃣ Proven ETL & Data Pipeline Development✔ Ability to design, implement, and optimise real-time & batch ETL pipelines✔ Strong understanding of data ingestion, transformation, and lineage tracking4️⃣ AI/ML Engineering Fundamentals (2+ Years in Production ML Systems)✔ Understanding of feature engineering, supervised ML, overfitting, and evaluation metrics✔ Experience working with MLFlow, Feature Stores, and AI-driven analytics5️⃣ Enterprise-Level Consulting & Leadership Experience✔ Experience collaborating with C-suite and business stakeholders to drive data strategy✔ Ability to mentor engineering teams and set best practices for scalability & automation

Created: 2025-03-07