Data Architect (Full-Time Only)

Job Title: Data Architect

Location: Atlanta, GA (On-site - Hybrid)

Essential functions:

1. Data Architecture & Engineering:

• Design and implement medallion architecture (raw, silver, gold layers) to enable efficient data ingestion, processing, and quality management.
• Develop standardized ETL and streaming pipelines using Databricks, Apache Spark, and Apache Airflow, ensuring low-latency data processing.
• Define and enforce data quality and observability frameworks, integrating dashboards and monitoring tools to maintain high data integrity.
• Optimize data pipeline performance and infrastructure costs, identifying bottlenecks and areas for improvement.

2. Technical Leadership & Strategy:

• Lead the technical discovery and ongoing development, assessing current systems, identifying pain points, and defining the target state architecture.
• Provide technical recommendations and a roadmap for implementation, ensuring best practices in data engineering and architecture.
• Guide the selection and implementation of cloud-based data platforms to support scalability, efficiency, and future growth.
• Ensure compliance with security, governance, and regulatory requirements in data handling and processing.

3. Cross-Team Collaboration & Stakeholder Engagement:

• Act as the technical point of contact between engineering teams, business stakeholders, and management.
• Work closely with team members to ensure smooth collaboration and knowledge transfer.
• Translate business requirements into technical solutions, ensuring alignment between data engineering practices and business objectives.

4. Project Delivery & Execution:

• Define best practices, coding standards, and development workflows for data engineering teams.
• Ensure a smooth transition from discovery to implementation, providing hands-on guidance and technical oversight.
• Participate in planning and work closely with the Delivery Manager to manage timelines and priorities, various program-related topics
• Monitor and troubleshoot data pipeline performance, ensuring high availability and reliability of data systems.

Qualifications:

• Cloud provider: AWS
• Programming language: Python
• Frameworks and technologies: AWS Glue, Apache Spark, Apache Kafka, Apache Airflow
• Experience working with on-premise will be a plus
• Azure Databricks is a MUST

Would be a plus:

• Data Engineering & Architecture: Deep experience with data platforms, specifically using Databricks, Apache Spark, and Apache Airflow.
• Proven capability in designing and implementing medallion architectures (raw, silver, gold).
• ETL Frameworks & Ingestion Patterns: Ability to establish standard ingestion patterns and create a uniform ETL framework for both batch and streaming data.
• Data Quality & Observability: Experience in setting up data quality frameworks, developing dashboards, and implementing observability tools to ensure data integrity.