Enterprise Data Architect – AWS, Databricks

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November 21

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Aptus Data Labs

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Artificial Intelligence • SaaS • B2B

Aptus Data Labs is a data engineering and enterprise AI company that builds scalable AI platforms, generative intelligence solutions, and data modernization services for large organizations. The company delivers industry-focused AI and analytics products (including aptplan, aptGenAI and other platforms) and services—covering advisory, cloud migration, MLOps/LLMOps, AI governance, and on-demand talent—to help pharmaceutical, banking, manufacturing, retail and other enterprises accelerate decision-making, compliance, and operational efficiency. Aptus partners with cloud and AI providers, offers pre-built accelerators and IP, and focuses on B2B deployments and enterprise-scale SaaS solutions.

201 - 500 employees

Founded 2014

🤖 Artificial Intelligence

☁️ SaaS

🤝 B2B

📋 Description

• Lead the enterprise data architecture strategy • Architect and implement data lakehouse solutions using Databricks on AWS • Design end-to-end data pipelines, integration frameworks, and governance models • Define data models, metadata management, and data quality frameworks • Collaborate with data engineering, AI/ML, analytics, and business teams • Evaluate and integrate emerging technologies in data mesh and automation frameworks • Provide technical leadership and mentorship to data engineering and architecture teams • Establish best practices for data security, lineage, compliance, and cloud cost optimization • Partner with business stakeholders to define data modernization roadmaps and cloud migration strategies

🎯 Requirements

• 18+ years of experience • Strong experience in Data Architecture, Data Engineering, or related domains • Proven experience architecting enterprise-scale data platforms using AWS • Hands-on expertise in Databricks (Delta Lake, Spark, Unity Catalog, MLflow) • Strong experience with data modeling and ETL/ELT pipelines • Deep understanding of data governance, master data management, and data cataloging tools • Proficient in SQL, Python, PySpark, and API-based data integration • Experience with modern data stack (Snowflake, dbt, Airflow, Kafka, etc.) is a plus • Strong understanding of AI/ML data readiness and metadata design • Excellent communication and leadership skills to collaborate with technical and business teams • Certifications in AWS or Databricks preferred

🏖️ Benefits

• Health insurance • Paid time off • Flexible work hours • Professional development opportunities