Data Architect

Compunnel, Inc.; Issaquah (WA); On-site; USD 120,000 - 150,000; Full time

Job summary

A leading technology consulting firm is seeking a Data Architect to modernize data ecosystems. The ideal candidate will lead legacy system upgrades, ensure data governance, and design scalable data solutions across cloud environments. Strong proficiency in data integration, cloud technologies, and relational databases is required.

Qualifications

• Proven experience in legacy modernization and transactional database architecture.
• Deep knowledge of data lakes, data warehouses, and real-time data pipelines.
• Strong proficiency in designing enterprise data solutions on cloud platforms.

Responsibilities

• Lead the upgrade, migration, and decommissioning of legacy database systems.
• Establish data governance frameworks covering data quality and retention.
• Design and manage integration of transactional databases with applications.

Skills

Data lifecycle management

Data integration

Data governance

Performance tuning

Analytical abilities

Documentation skills

Python

SQL

Java

NoSQL databases

Education

Architect or Big Data specialty certification in AWS, Azure, or GCP

Tools

MySQL

Oracle

PostgreSQL

AWS

Azure

GCP

Job description

The Data Architect will lead the modernization and transformation of data ecosystems, including legacy transactional databases and large-scale enterprise data platforms.

This role involves architecting scalable, resilient, and secure data solutions across cloud, big data, and enterprise environments.

The position requires deep expertise in data lifecycle management, real-time integration, governance, analytics, and cloud-based data services to support operational, analytical, and strategic business needs.

Key Responsibilities

Lifecycle Management

• Lead the upgrade, migration, and decommissioning of legacy transactional database systems.
• Align data lifecycle processes with organizational retention, archiving, and compliance policies.

Documentation & Standards

• Develop comprehensive documentation for database architectures, data models, and operational frameworks.
• Define and promote best practices for database development, maintenance, and operations.

Integration & Data Flow

• Design and manage integration of transactional databases with enterprise applications.
• Define real-time ingestion, streaming, and consumption patterns for consistent data flow.

Data Governance & Security

• Establish governance frameworks covering data quality, retention, classification, and archiving.
• Implement robust security including access management, encryption, and auditing.

Performance Tuning & Scalability

• Diagnose and resolve performance issues in transactional systems.
• Implement scaling strategies such as clustering, sharding, indexing, and connection pooling.
• Evaluate relational database technologies (MySQL, Oracle, PostgreSQL) based on application needs.
• Design highly available architectures supporting disaster recovery and replication.
• Build conceptual, logical, and physical data models ensuring normalization and referential integrity.
• Optimize schemas using indexing strategies, appropriate data types, and selective denormalization.
• Architect and implement high-performance data integration, data warehouses, data lakes, and analytics solutions.
• Design big data solutions on AWS, Azure, or GCP using technologies like Hadoop, Spark, Kafka, Hive, Flume, Sqoop, Pig, etc.
• Develop data analysis solutions including predictive models, statistical analysis, and graph-based insights.
• Implement data virtualization and integrate with platforms for data science and data services.
• Develop long-term data architecture strategies and short-term tactical solutions.
• Establish processes for metadata management, data quality tracking, and regulatory compliance.
• Ensure enterprise needs in operational and reporting data are met.

Operational Management

• Establish data governance, stewardship models, and data management methodologies.
• Select and implement appropriate technologies supporting enterprise data goals.
• Collaborate with PMs and business teams to solve data-related integration and compatibility issues.
• Document and maintain the enterprise data architecture landscape.

Project Review & Optimization

• Conduct architecture reviews and provide optimization insights on cost, time, and quality.
• Support teams with technical consultations and audits for complex projects.

Knowledge Management & Capability Development

• Conduct internal training, create learning materials, and build domain expertise.
• Collaborate with internal centers of excellence to develop training programs and reusable assets.

Requirement Gathering & Analysis

• Understand cross-functional requirements and validate integration and reconciliation needs.

People Management

• Support training needs assessment, conduct workshops, mentor teams, and assist in technical evaluations.

Alliance Management

• Develop joint offerings with technology partners and act as technical POC for solutions.
• Define customer problem statements, analyze landscapes, propose solution options, and build roadmaps.
• Perform cost-benefit analysis and present findings to stakeholders.

Innovation & Thought Leadership

• Participate in seminars, present research, create IP, reusable patterns, accelerators, and white papers.
• Support RFP responses, compare designs, provide estimations, and participate in client workshops.

Data Design & Definition

• Ensure architectural alignment with business logic and involve appropriate teams in design.
• Provide guidance on data architecture, migration, integration, and cloud/hosted solutions.
• Maintain architecture principles and identify efficiency opportunities.

Project Management Support

• Identify and manage technical risks proactively.

Stakeholder Management

• Build credibility as the technical go-to expert and expand networks within client organizations.

New Service Design

• Identify opportunities for new service offerings, co-develop GTM strategies, build frameworks, and perform beta testing.

Required Qualifications

• Proven experience in legacy modernization and transactional database architecture.
• Strong understanding of ACID principles and relational databases (MySQL, Oracle, PostgreSQL).
• Deep knowledge of data integration, data lakes, data warehouses, and real-time data pipelines.
• Strong proficiency in designing enterprise data solutions on AWS, Azure, or GCP.
• Expertise in performance tuning, indexing, scalability strategies, and secure data practices.
• Strong analytical abilities with attention to detail.
• Excellent documentation, communication, and customer-facing skills.
• Proficiency in Python, Java, SQL, and working with NoSQL databases.
• Experience with data modeling, metadata management, data governance, and data quality frameworks.
• Experience in cloud architectures, backup/archival tools, and data security best practices.

Preferred Qualifications

• Experience with AI/ML models, graph databases, and tools like Lucene, Gephi.
• Knowledge of domain-specific data (Retail, Healthcare, Banking, Finance).
• Experience conducting workshops, leading strategy discussions, and presenting to customers.
• Prior involvement in speaking engagements, white papers, or patent applications.
• Strong experience with enterprise-level estimation, RFP responses, and sales support.
• Familiarity with innovation labs, beta testing, accelerators, and reusable design components.

Certifications

• Architect or Big Data specialty certification in AWS, Azure, or GCP.