Data Architect - Atlanta

Only for registered members Atlanta, United States

10 hours ago

$115,000 - $170,000 (USD) per year *

* This salary range is an estimation made by beBee

Dice is the leading career destination for tech experts at every stage of their careers. Our client, Agile / Access Data, is seeking the following. Apply via Dice today · Location Hybrid Remote in Atlanta (3 days onsite/week). · Note: · Initial 100% onsite required for the first ...

Job description

Dice is the leading career destination for tech experts at every stage of their careers. Our client, Agile / Access Data, is seeking the following. Apply via Dice today

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 $180,000 (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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