Agile
Data Architect
Location :
Hybrid Remote in Atlanta (3 days onsite / week). Initial 100% onsite required for the first six months.
Employment Type :
Permanent / Direct Hire / Full-time
Salary : Up to $160,000 (depending on experience) + bonus
We're seeking a highly skilled and hands‑on Senior Data Architect to lead the design, implementation, and ongoing evolution of our enterprise‑grade data systems. This role is crucial for building scalable, secure, and intelligent data infrastructure that supports core analytics, operational excellence, and future AI initiatives. Success requires a seasoned technologist who can seamlessly integrate cloud‑native services with traditional data warehousing to create a modern, unified data platform.
Here's what you'll be doing :
Architecture & Strategy : Lead the design and implementation of modern data platforms, including Data Lakes, Data Warehouses, and Lakehouse architectures, to enable a single source of truth for the enterprise.
Data Modeling & Integration : Architect unified data models that support both modular monoliths and microservices‑based platforms. Design and optimize high‑volume, low‑latency streaming / batch ETL / ELT pipelines.
Technical Leadership : Drive the technical execution across the entire data lifecycle. Build and optimize core data processing scripts using Spark and Python.
Governance & Quality : Define and enforce standards for data governance, metadata management, and data observability across distributed systems. Implement automated data lineage tracking, schema evolution, and data quality monitoring.
Cloud Infrastructure : Configure and manage cloud‑native data services, including core data storage and event ingestion infrastructure.
Here's what our ideal candidate has :
Experience : 10+ years of proven experience in enterprise data architecture and engineering.
Core Platform Expertise : Strong, hands‑on experience with the Azure Data Ecosystem including Azure Data Lake Storage (ADLS), Azure Synapse Analytics (or equivalent cloud DW), and Azure Purview (or equivalent data catalog).
Processing : Deep expertise in Databricks (or Apache Spark) for ETL / ELT pipeline implementation, using Delta Lake and SQL Server (or equivalent RDBMS).
Coding & Scripting : Strong proficiency in Python, Spark, and advanced SQL.
Data Governance : Hands‑on experience implementing data lineage tracking and data quality monitoring (e.g., using Great Expectations or dbt).
Semantic Technologies : Hands‑on experience developing ontology frameworks using OWL, RDF, and SPARQL to enable semantic interoperability.
Advanced AI Data : Experience integrating structured / unstructured data into Knowledge Graphs and Vector Databases.
Streaming / Telemetry : Experience developing and maintaining semantic telemetry pipelines using services like Azure Event Hubs or Kafka.
Emerging Concepts :
Exposure to linked data ecosystems, data mesh, or data fabric concepts.
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Location :
Hybrid Remote in Atlanta (3 days onsite / week). Initial 100% onsite required for the first six months.
Employment Type :
Permanent / Direct Hire / Full-time
Salary : Up to $160,000 (depending on experience) + bonus
We're seeking a highly skilled and hands‑on Senior Data Architect to lead the design, implementation, and ongoing evolution of our enterprise‑grade data systems. This role is crucial for building scalable, secure, and intelligent data infrastructure that supports core analytics, operational excellence, and future AI initiatives. Success requires a seasoned technologist who can seamlessly integrate cloud‑native services with traditional data warehousing to create a modern, unified data platform.
Here's what you'll be doing :
Architecture & Strategy : Lead the design and implementation of modern data platforms, including Data Lakes, Data Warehouses, and Lakehouse architectures, to enable a single source of truth for the enterprise.
Data Modeling & Integration : Architect unified data models that support both modular monoliths and microservices‑based platforms. Design and optimize high‑volume, low‑latency streaming / batch ETL / ELT pipelines.
Technical Leadership : Drive the technical execution across the entire data lifecycle. Build and optimize core data processing scripts using Spark and Python.
Governance & Quality : Define and enforce standards for data governance, metadata management, and data observability across distributed systems. Implement automated data lineage tracking, schema evolution, and data quality monitoring.
Cloud Infrastructure : Configure and manage cloud‑native data services, including core data storage and event ingestion infrastructure.
Here's what our ideal candidate has :
Experience : 10+ years of proven experience in enterprise data architecture and engineering.
Core Platform Expertise : Strong, hands‑on experience with the Azure Data Ecosystem including Azure Data Lake Storage (ADLS), Azure Synapse Analytics (or equivalent cloud DW), and Azure Purview (or equivalent data catalog).
Processing : Deep expertise in Databricks (or Apache Spark) for ETL / ELT pipeline implementation, using Delta Lake and SQL Server (or equivalent RDBMS).
Coding & Scripting : Strong proficiency in Python, Spark, and advanced SQL.
Data Governance : Hands‑on experience implementing data lineage tracking and data quality monitoring (e.g., using Great Expectations or dbt).
Semantic Technologies : Hands‑on experience developing ontology frameworks using OWL, RDF, and SPARQL to enable semantic interoperability.
Advanced AI Data : Experience integrating structured / unstructured data into Knowledge Graphs and Vector Databases.
Streaming / Telemetry : Experience developing and maintaining semantic telemetry pipelines using services like Azure Event Hubs or Kafka.
Emerging Concepts :
Exposure to linked data ecosystems, data mesh, or data fabric concepts.
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