Architect Data Architecture

Overview

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.

What you'll do

• 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.

What you'll need

• 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

• 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).

Details

• Location: Bangalore, Karnataka, India.