Analytics Engineer

Job Description

Analytics Engineer Affirma, five years in a row ranked "Best Companies to Work for" and "Fastest Growing Companies" in Washington is seeking an Analytics Engineer to join our growing Data & Analytics team. This individual will support Affirma’s mission to provide exception value to our clients by planning, executing, and deploying data management solutions. Qualifications

• 5+ years of professional experience in analytics engineering, dimensional data modeling, ETL/ELT development, medallion architecture, and data warehousing.
• Hands-on experience with modern data engineering and analytics technologies, particularly within the Azure, AWS, Snowflake, GCP, Databricks, etc.
• Advanced proficiency in T-SQL and strong Python skills for data transformation, automation, complex queries, stored procedures, functions, data validation, and performance optimization.
• Strong understanding of relational databases, dimensional modeling, star and snowflake schemas, fact and dimension tables, and database design best practices.
• Experience designing and implementing scalable data warehouses, lakehouses, and analytics-ready data models that support reporting, business intelligence, and downstream analytics.
• Demonstrated ability to integrate data from multiple disparate sources into trusted, consistent, and well-documented data models that serve as a unified source of truth.
• Experience implementing data transformation and orchestration processes, including incremental data loading, error handling, data reconciliation, and pipeline monitoring.
• Knowledge of data quality, testing, validation, and reconciliation practices to ensure the accuracy, consistency, completeness, and reliability of data.
• Experience optimizing SQL queries, data models, and data processing workflows for performance, scalability, and maintainability.
• Understanding of data governance, security, access controls, and the responsible handling of sensitive business information.
• Ability to translate business and technical requirements into practical data solutions while working in a dynamic environment with ambiguity and minimal supervision.
• Strong analytical and problem-solving skills, with the ability to investigate data issues, identify root causes, and recommend sustainable solutions.
• Excellent written and verbal communication skills, including the ability to collaborate with technical teams, business stakeholders, and clients and maintain clear technical documentation.
• Ability to manage multiple priorities, meet project deadlines, and communicate progress, risks, dependencies, and changes proactively. Responsibilities
• Design, develop, and maintain scalable data engineering and analytics solutions, including data warehouses, lakehouses, data pipelines, analytics-ready data models, data viz and models.
• Translate business requirements and reporting needs into effective data architectures, dimensional models, transformation logic, and reusable data assets.
• Develop and maintain ETL/ELT pipelines to extract, integrate, transform, validate, and deliver data from multiple source systems.
• Implement and maintain medallion architecture patterns, including bronze, silver, and gold data layers, where appropriate to the client's environment.
• Build and maintain dimensional data models, including fact tables, dimension tables, conformed dimensions, and other structures that support consistent business reporting.
• Develop, review, debug, and optimize SQL queries, Python scripts, stored procedures, and data transformation processes.
• Develop visualization reporting in available tools.
• Support the deployment and release of data solutions into production environments, including testing, validation, documentation, and post-release support.
• Create and maintain technical documentation describing data architecture, source-to-target mappings, transformation logic, dependencies, testing procedures, and ongoing maintenance requirements.
• Apply data engineering and analytics best practices to produce secure, scalable, reusable, and maintainable solutions.
• Provide technical guidance and support to data consumers, analysts, and other stakeholders regarding data availability, quality, definitions, and reporting issues.
• Contribute to solution design discussions and provide recommendations on tools, architecture, data modeling, performance, and implementation approaches.
• Balance shifting priorities, project demands, and delivery timelines while communicating status, risks, dependencies, and expectations clearly and proactively.
• Continuously develop technical expertise in modern data platforms, analytics engineering practices, cloud technologies, and emerging data and AI capabilities.

Accountabilities and Measures

• Client satisfaction: Deliver reliable, high-quality solutions that meet client requirements and support measurable business outcomes.
• Delivery quality: Produce accurate, tested, performant, secure, and maintainable data solutions while minimizing defects and avoidable rework.
• Collaboration: Work effectively with internal teams, client stakeholders, architects, analysts, and other delivery resources.
• Communication: Provide timely updates, document technical decisions, communicate risks and blockers, and set clear expectations with stakeholders.
• Project execution: Complete assigned work within agreed scope, timelines, and quality standards while escalating risks and dependencies early.
• Data quality and reliability: Ensure appropriate validation, reconciliation, testing, and monitoring practices are incorporated into delivered solutions.
• Maintainability and documentation: Create reusable data assets and maintain documentation sufficient for other team members to understand, support, and extend the solution.
• Commercial and operational alignment: Adhere to Affirma's timekeeping, billable and non-billable policies, project procedures, and client engagement expectations.
• Continuous improvement: Identify opportunities to improve engineering standards, delivery efficiency, data quality, performance, and reusable delivery practices.
• Professional development: Continuously expand technical knowledge and apply relevant best practices to client engagements.
• Remote Work: Must adhere to camera on policy, in internal and client meetings
• Must be able to travel <10%

Affirma is an Equal Opportunity Employer and does not make employment decisions or otherwise discriminates based on race, creed, color, national origin, sex, military status, sexual orientation, or the presence of any sensory, mental, or physical disability, genetic information, or any other category protected by law.