Principal Duties & Responsibilities • Architect end to end data solutions and provide implementation oversight in alignment with enterprise architecture standards. • Rapidly assess the current data landscape and identify gaps, risks, and opportunities to accelerate modernization. • Deliver actionable architecture artifacts—including data models, integration patterns, and platform designs—under compressed timelines. • Enhance foundational data capabilities such as ingestion pipelines, domain models, metadata frameworks, and data quality structures. • Define, document, and promote scalable architecture patterns for immediate adoption by engineering teams. • Partner closely with architects, engineers, and business stakeholders to translate requirements into actionable designs that fit enterprise standards. • Provide hands on architectural leadership for high priority initiatives, ensuring solutions are modern, scalable, and aligned with enterprise principles while enabling speed. • Introduce external best practices across cloud, data mesh, event driven architectures, and AI/ML enabled solutions. • Advise on platform/tooling selections and modernization pathways grounded in real industry experience and time to value. • Produce clear documentation, decision records, and transition materials to enable seamless handoff to full time teams. ________________________________________ Knowledge & Skills • Broad understanding of IT systems and how business processes interact with applications, databases, storage platforms, security, and networks. • Deep experience with relational and non-relational databases, including but not limited to DynamoDB and Neptune. • Strong experience designing and implementing Data APIs using cloud technologies; MuleSoft experience is a plus. • Expertise in data movement, data quality enforcement, and cloud based data processing. • Prior experience architecting fault tolerant, self-healing, highly scalable, or multi-tenant data systems. • Strong understanding of data management patterns and best practices. • Familiarity with enterprise and service design patterns, including practical application of Data Mesh and Data Product paradigms. • Ability to design flexible systems and adopt new or emerging technologies as appropriate. • Comfortable operating with minimal supervision in a complex hybrid environment. • Brings industry knowledge from working across multiple organizations or modern data intensive transformations. • Recommends best practices based on cloud adoption patterns, analytics needs, and AI/ML readiness. • Able to challenge existing approaches and introduce new, reusable patterns. • Capable of producing high clarity architecture artifacts (decision records, diagrams, standards) that can be adopted immediately. • Understanding of modern data ingestion and transformation patterns (streaming, batch, CDC). • Familiarity with data pipeline frameworks, orchestration tools, and platform services (Spark, Kafka, Snowflake, Databricks, Glue, Airflow, etc. • Ability to quickly assess complex data ecosystems and recommend modernization paths. • Strong understanding of cloud-based data architectures (AWS), Data mesh patterns, and modern data stack components. Contact Information Email: dhanraj.saliyan@bravensinc.com Click the email address to contact the job poster directly. Related