Enterprise Data Architect

Company Description

Aptus Data Labs

Job Title: Enterprise Data Architect (AWS)

Experience

Location

Employment Type: Full-time

Notice

About the Role:

Enterprise Data Architect

Key Responsibilities:

• Lead the enterprise data architecture strategy, ensuring scalability, performance, and alignment with business goals.
• Architect and implement data lakehouse solutions using Databricks on AWS for unified data management and analytics.
• Design end-to-end data pipelines, integration frameworks, and governance models across structured and unstructured data sources.
• Define data models, metadata management, and data quality frameworks for enterprise-wide adoption.
• Collaborate with data engineering, AI/ML, analytics, and business teams to enable real-time and batch data processing.
• Evaluate and integrate emerging technologies in data mesh, GenAI data pipelines, and automation frameworks.
• Provide technical leadership and mentorship to data engineering and architecture teams.
• Establish best practices for data security, lineage, compliance (GDPR, HIPAA), and cloud cost optimization.
• Partner with business stakeholders to define data modernization roadmaps and cloud migration strategies.

Required Skills and Experience:

• 10-15 years IT experience with 5-8 years enterprise data architect
• Strong experience in Data Architecture, Data Engineering, or related domains.
• Proven experience architecting enterprise-scale data platforms using AWS (S3, Glue, Lambda, Redshift, EMR, Athena, Lake Formation, etc.).
• Hands-on expertise in Databricks (Delta Lake, Spark, Unity Catalog, MLflow).
• Strong experience with data modeling (dimensional, canonical, semantic models) and ETL/ELT pipelines.
• Deep understanding of data governance, master data management (MDM), 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, metadata design, and data observability frameworks.
• Excellent communication and leadership skills to collaborate with technical and business teams.
• Certifications in AWS (Data Analytics / Solutions Architect) or Databricks preferred.
• Experienced in global onsite client handling role and managing senior management stakeholder interactions

Preferred Qualifications:

• Experience in enterprise data strategy, governance frameworks, and migration of legacy systems to cloud.
• Exposure to GenAI data pipelines or LLM-based data preparation workflows.
• Strong background in data security, IAM, and compliance standards.

Education:

Bachelor’s or master’s degree in computer science, Information Systems, Data Engineering, or related field.