Job Summary 
As a Data Architect at Empower, you will be a hands-on technical expert and solution shaping architecture contributor, helping design the company’s cloud and data architecture. Partnering with enterprise architects, senior architects, business leaders, and IT teams, you will define solution architectures and support modernization initiatives aligned with Empower’s vision for performance, efficiency, and cost optimization. You will also partner with Empower’s Innovation Lab to explore emerging technologies including Generative AI and Advanced Analytics, translating experimentation into practical patterns and recommendations for delivery teams. You will influence architectural decisions, contribute to team standards and governance, and help elevate technology excellence through consistent, high quality designs. 

Responsibilities 

• Partner with Enterprise Architects, Senior Architects, and cross functional teams including business stakeholders to shape solution architectures aligned to a unified IT data strategy. 

• Contribute to Empower’s technology roadmap by documenting target state architectures, reference architectures, and key dependencies for supported initiatives. 

• Design and support modernization and migration of complex systems to scalable, secure, and cost optimized cloud architectures, working with delivery teams through implementation. 

• Evaluate and prototype new technologies and applications, challenge existing approaches constructively, and provide input into business cases and recommendations. 

• Apply and help operationalize architectural standards, best practices, and governance expectations, supporting consistent adoption through guidance and enablement. 

• Collaborate closely with business and engineering teams to design end to end solutions that meet strategic, technical, and operational objectives. 

• Provide architectural guidance in process design, system orchestration, and enterprise integration to enable cohesive and efficient technology ecosystems. 

• Champion security, resilience, and scalability as core design principles across data platforms and data solutions. 

• Contribute to architecture discipline maturity by producing reusable patterns, decision documentation, and lessons learned that improve consistency and delivery speed. 

• Support full stack development teams through solution design and implementation, improving long term scalability, performance, and cost outcomes. 

Required Skills 

• At least 5 years of experience delivering data-intensive solutions (for example in data engineering, analytics engineering, data platforms, BI, or related roles). 

• At least 1 year of demonstrated solution design ownership for moderately complex initiatives, gained as an architect or as a senior engineer/technical lead responsible for end-to-end design, architectural trade-offs, and guiding implementation. 

• Proven experience in multiple data focused roles including Data Engineer (ETL/ELT), Data Architect, Database Administrator, BI or Analytics Engineer, Data Science, data governance, or a similar field. 

• Competency in architecture frameworks, performance optimization, and addressing cross cutting concerns including availability, caching, monitoring, scalability, and security. 

• Strong problem solving and strategic thinking, with the ability to influence cross functional teams and communicate architecture decisions clearly in distributed environments. 

• Strong expertise in designing data and cloud architecture, AWS preferred, supporting scalability, performance, and security with systems such as Snowflake or Redshift. 

• Proven ability to translate complex data into actionable business insights and reporting solutions that provide comprehensive and up to date information to business users. 

• Bachelor’s degree in Computer Science, Information Systems, or related discipline, or equivalent practical experience. 

Nice to Have Qualifications 

• Data engineering experience designing and delivering ETL and ELT pipelines, including orchestration, data quality controls, and reliable operations for batch and near real time workloads. 

• Streaming and event driven data experience building and operating Kafka or Kinesis based architectures including ordering, replay, schema evolution, and real time observability. 

• API and integration experience designing API first data access patterns, API lifecycle governance, versioning, security, and developer enablement, plus event driven integration patterns to reduce point to point complexity. 

• Data platform modernization experience designing large scale ingestion and processing platforms using Spark or comparable distributed compute and orchestrating reliable batch and near real time pipelines. 

• Data security and privacy experience implementing encryption, masking or tokenization, access controls, and auditability patterns for sensitive data and regulated environments. 

• Cloud cost and performance experience applying FinOps practices, workload right sizing, storage optimization, and performance engineering for cloud data platforms. 

• DevOps for data experience building CI/CD for data pipelines, infrastructure as code practices, and container platforms such as Kubernetes or EKS for data workloads. 

• Applied AI and GenAI experience designing safe enterprise patterns for retrieval, evaluation, monitoring, and responsible AI adoption. 

• Broad polyglot engineering experience with Java, microservices patterns, and third party API integrations that support data intensive services. 

• Certifications such as AWS Certified Solutions Architect (Associate or Professional). 

Education 

• Bachelor’s and/or master’s degree in computer science or related field (information systems, mathematics, software engineering, etc.) 

Physical Requirements/Working Conditions 

• Normal Office Working Conditions