Data Architect

Socket.dev

West Des Moines (IA)

On-site

USD 120,000 - 160,000

Full time

5 days ago
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Job summary

Socket.dev is seeking an experienced Data Architect/Data Engineer to own enterprise data architecture across analytical, operational, and integration platforms in a Microsoft Azure environment. You will design data models, build scalable data pipelines, and collaborate with business, analytics, security, and applications teams to deliver compliant, high-quality data solutions.

The role requires 8+ years of experience in data architecture/engineering, strong SQL and Python skills, and hands-on

Qualifications

  • Bachelor's degree in computer science, information systems, engineering, or equivalent experience.
  • 8+ years of experience in data architecture and/or data engineering roles.

Responsibilities

  • Define and own enterprise data architecture across analytical, operational, and integration platforms.
  • Design scalable cloud-based and hybrid data platforms (data lakes, lakehouses, warehouses).
  • Partner with business, analytics, security, and application teams to translate requirements into data solutions.
  • Design and build robust data pipelines (batch and streaming) for ingestion, transformation, and delivery.
  • Develop and optimize ETL/ELT processes using modern data engineering frameworks.
  • Design logical, physical, and conceptual data models to support analytics, reporting, AI/ML, and operations.

Skills

Azure Data Lake Gen2
Azure Synapse Analytics
Azure Data Factory
Azure Databricks
Python
Advanced SQL
Data Modeling
Stakeholder Communication

Education

Bachelor's degree in CS/IS/Engineering

Tools

Power BI

Job description

ESSENTIAL DUTIES AND RESPONSIBILITIES:

Data Architecture (≈70%)

  • Define and own enterprise data architecture across analytical, operational, and integration platforms
  • Design logical, physical, and conceptual data models to support analytics, reporting, AI/ML, and operational use cases
  • Establish and enforce data architecture standards, patterns, and best practices
  • Design scalable cloud-based and hybrid data platforms (e.g., data lakes,lakehouses, warehouses)
  • Partner with business, analytics, security, and application teams to translate requirements into data solutions
  • Ensure data solutions align with security, governance, privacy, and compliance requirements
  • Lead architecture reviews andprovidetechnical guidance to data engineers and analytics teams
  • Evaluate and recommend data technologies, tools, and platforms
  • Ensuredata governance, metadata management, data quality, and lineage initiatives

Data Engineering (≈30%)

  • Design and build robust data pipelines (batch and streaming) for ingestion, transformation, and delivery
  • Develop andoptimizeETL/ELT processes using modern data engineering frameworks
  • Collaborate with engineers to implement architectural patterns in production systems
  • Ensure pipelines are reliable, scalable, performant, and cost-efficient
  • Troubleshoot data issues andoptimizequeries, storage, and processing
  • Support CI/CD practices, automated testing, and monitoring for data workflows

EDUCATION, TRAINING, AND EXPERIENCE:

  • Bachelor's degree in computer science, Information Systems, Engineering, or equivalent experience
  • 8+ years of experience in data architecture and/or data engineering roles

REQUIRED SKILLS:

  • Proven experience designing enterprise-scale Azure
  • Strong hands-on experience with:
  • Azure Data Lake Storage Gen2
  • Azure Synapse Analytics
  • Azure Data Factory
  • Azure Databricks or Microsoft Fabric
  • Advanced SQL skills and experience with Python (preferred)
  • Strong knowledge of data modeling, performance tuning, and cost optimization in Azure
  • Experience integrating data from SaaS, on-prem, and cloud-based systems
  • Ability to clearly communicate architectural decisions to both technical and non-technical stakeholders
  • Background with Data Governance Framework

Preferred Skills:

  • Experience designing data architectures that support AI and machine learning workloads, including feature engineering, training, inference, and monitoring at scale.

TOOLS, EQUIPMENT, AND SOFTWARE:

  • Experience with Microsoft Fabric (OneLake, Lakehouse, Warehouse, Power BI integration)
  • Familiarity with Power BI semantic models and analytics consumption patterns
  • Knowledge of Azure Purview / Microsoft Purview for data governance and lineage
  • Experience with event-driven and streaming architectures in Azure
  • Understanding ofDataOps/ DevOps practices in an Azure environment
  • Experience supporting regulated or security-conscious enterprise environments

WORKING CONDITIONS AND PHYSICAL REQUIREMENTS:

  • Primarily indoor work in an office environment requiringlong periodsof sitting
  • Frequentutilizationof manual dexterity and visualizing of a computer screen
  • No unusual physical requirements
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