Data Architect

  • Atlanta, GA
  • Posted 2 days ago | Updated 2 days ago

Overview

Hybrid
Up to $160,000
Full Time
No Travel Required

Skills

Azure
Azure Data Lake
ADLS
Azure Synapse
Synapse Analytics
Azure Purview
Databricks
Apache Spark
Spark SQL
Delta Lake
SQL Server
RDBMS
Python
PySpark
SQL
ETL
ELT
data pipelines
data engineering
data architecture
data modeling
data warehousing
data lakehouse
cloud architecture
Azure Functions
Azure Event Hubs
Kafka
data governance
data lineage
data catalog
metadata management
data observability
data quality
Great Expectations
dbt
schema evolution
semantic technologies
ontology
OWL
RDF
SPARQL
knowledge graph
vector database
AI data integration
streaming data
telemetry
data mesh
data fabric
linked data
DevOps
CI/CD
Git
version control
JSON
Parquet
Power BI
REST APIs
Azure DevOps
MLOps

Job Details

Location Hybrid Remote in Atlanta (3 days onsite/week).

Note: 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

The Role:

We're seeking a highly skilled and hands-on 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.

What You'll Do:

  • 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.

Required Experience:

  • 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).

Preferred Skills:

  • 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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