System Architect

Title: System Architect

Location: Remote Position

Duration: 12+ Month Contract

Responsibilities:

Architecture & Technical Leadership

• Provide AWS and VAEC architecture leadership for an analytics team supporting VA LGY initiatives.
• Define end-to-end reference architectures, design patterns, and engineering standards for analytics solutions.
• Lead architecture reviews, ensuring solutions meet security, compliance, scalability, resiliency, and performance requirements.

Data Platform & Pipeline Design

• Architect and design data ingestion and transformation pipelines using EMR/Spark, AWS Glue, and related AWS services.
• Design and optimize Amazon Redshift architectures, including cluster sizing, distribution/sort keys, workload management, and query tuning.
• Create and maintain data models (conceptual/logical/physical) aligned to analytics and reporting use cases.

Performance Tuning & Reliability

• Tune Spark jobs and pipeline performance (e.g., partitioning strategy, executor sizing, shuffle optimization).
• Improve Redshift performance through schema design, query optimization, compression, and vacuum/analyze strategies.
• Establish monitoring, alerting, and runbooks for production operations; drive root-cause analysis and continuous improvement.

Client Advisory & Solutioning

• Identify gaps or problems in client systems and assess technical needs against business strategy.
• Develop solution options, including trade-off analysis and cost implications (e.g., compute/storage choices, workload patterns).
• Produce plans and diagrams showing how solutions will work and present them in an understandable way to technical and non-technical audiences.

Governance, Security & Compliance

• Ensure architecture aligns with required industry regulations and security standards (e.g., data handling, access controls, auditing).
• Partner with security and governance stakeholders to implement data protection, least privilege, and data lifecycle management practices.

Collaboration & Stakeholder Management

• Provide coaching and technical direction to team members; elevate engineering practices through standards and code/design reviews.
• Maintain ongoing relationships with clients and internal partners; provide timely feedback to production teams to improve delivery outcomes.

Required Skills:

Bachelor s degree

AWS & Analytics Architecture

Strong experience designing analytics solutions on AWS, including services such as:

EMR (Spark), AWS Glue, Amazon Redshift, S3, IAM, CloudWatch

Hands-on experience with data pipeline architecture (batch and/or near-real-time), orchestration, and production operations.

Data Engineering & Modeling

Proficiency in Spark (PySpark/Scala) and SQL; strong grasp of distributed data processing concepts.

Experience with data modeling (dimensional modeling, star/snowflake patterns, normalization trade-offs).

Strong SQL skills for performance analysis and tuning (query plans, indexing concepts where applicable, join strategies).

Performance & Cost Optimization

Demonstrated experience with performance tuning for Spark workloads and Redshift queries.

Ability to evaluate and communicate cost implications of architecture choices; implement cost controls and optimization strategies.

Delivery & Documentation

Ability to create clear architecture diagrams, solution documents, and operational runbooks.

Experience collaborating in Agile delivery models and partnering across engineering, product, and operations teams.

Preferred Skills

Experience with VAEC environments, government cloud implementations, or regulated enterprise environments.

AWS certifications (preferred): Solutions Architect, Data Analytics, Security, or DevOps Engineer.

Infrastructure as Code (IaC): Terraform, CloudFormation, and CI/CD automation.

Data governance and cataloging tools (e.g., data lineage, metadata management) and best practices.

Experience with data quality frameworks, testing strategies, and schema evolution in data lakes/warehouses.

Familiarity with streaming/event-driven architectures (e.g., Kinesis/MSK) and/or lakehouse patterns.

Experience integrating BI tools and semantic layers for analytics consumption.

Soft Skills:

• Consultative communication: Ability to explain technical concepts and trade-offs to non-technical stakeholders clearly.
• Leadership without authority: Drives alignment, standards, and good decisions across teams through influence.
• Problem-solving mindset: Quickly isolates issues, identifies root causes, and proposes pragmatic solutions.
• Customer focus: Builds trust, listens actively, and incorporates feedback to improve outcomes.
• Ownership & accountability: Follows through from design to implementation to operational stability.
• Collaboration: Works effectively across architects, engineers, analysts, security, and business partners.
• Adaptability: Comfortable navigating ambiguity and iterating designs as requirements evolve.