5 Erds Jobs

You are a skilled System Architect with proven experience in designing and scaling SaaS platforms. You will play a critical role in translating product vision into scalable, secure, and maintainable architecture for products. Your responsibilities will involve architectural planning, technology decision-making, documentation & standards, collaboration, security & compliance, and performance & scalability. In terms of Architectural Planning, you will be required to design scalable, robust, and cloud-native architecture for SaaS platforms. This includes defining the system blueprint encompassing microservices, API layers, databases, and third-party integrations. Your role will involve making crucial Technology Decision-Making by selecting appropriate tech stacks and tools for backend, frontend, deployment, CI/CD, and monitoring. It is essential to evaluate trade-offs and maintain a balance between business needs and technical feasibility. Documentation & Standards play a vital role where you will be responsible for creating architecture documents, flow diagrams, and data models. Additionally, defining coding, security, and testing standards for the team will be part of your responsibilities. Collaboration is key as you will work closely with Product Owners, Developers, DevOps, and QA to ensure smooth implementation of the architecture. You will review and guide code and design decisions across teams to ensure alignment with the architecture. In terms of Security & Compliance, you will implement architecture that adheres to security best practices (OWASP, GDPR, ISO). Ensuring data protection and role-based access design from day one will be critical for the success of the platform. Performance & Scalability are crucial aspects where you will plan for load balancing, caching, latency optimization, and database optimization. Conducting performance testing and guiding mitigation strategies will be essential to maintain optimal platform performance. Your Required Skills include strong experience in SaaS application architecture, expertise in cloud platforms (AWS, GCP, or Azure), solid understanding of microservices, RESTful APIs, GraphQL, and event-driven systems, familiarity with database design (SQL and NoSQL) and data modeling, experience with DevOps practices, knowledge of security standards, and compliance frameworks for SaaS, and ability to create UML diagrams, sequence flows, and ERDs. Preferred Qualifications include hands-on experience with SaaS platforms in AdTech, SEO, or Martech domains, experience with multi-region deployments, autoscaling, and serverless architecture, working on legacy migrations or version upgrades of SaaS platforms, and familiarity with AI/ML integration in SaaS (a plus).,

Role: Data Solution Architect Location: Bangalore, Chennai, Hyderabad, Kochi, Mumbai, Kolkata, Noida, Gurgaon (Any office but he/she need to be local) Experience: 12-15 Years Budget: 35-40 LPA Only Immediate Joiners Role Objectives Design and maintain enterprise data architecture to support the analysis and interpretation of complex datasets from diverse sources, transforming them into actionable business insights. Lead deep technical investigations into complex data challenges to define solution architecture , propose target state models, and identify key benefits. Apply industry-standard templates, methodologies, and best practices for data architecture, integration, and governance. Implement enterprise data management capabilities including data catalogues , business glossaries , metadata management , data lineage , and reference/master data frameworks . Drive adoption of cloud-native platforms such as Azure Data Platform , Informatica , and automation tools for scalable data solutions. Architect automated data processing workflows using tools like Power Automate , Python , macros , and custom scripts to streamline data operations. Identify and implement data architecture optimizations for efficiency, performance, and scalability. Collaborate with cross-functional teams to enable data-driven decision-making through architectural guidance and scalable data solutions. Enforce and promote data management best practices and architectural governance standards. Stakeholder Management Partner with Product Owners and Data Governance Leaders to promote adoption and alignment of data architecture with business objectives. Ensure data solutions are understandable and usable by technical and non-technical stakeholders. Act as a data architecture evangelist , capturing feedback and driving continuous improvement. Governance and Compliance Operate in alignment with organizational policies, data standards, and regulatory requirements . Ensure adherence to enterprise data governance frameworks, policies, and audit controls . Essential Skills Strong experience as a Data Solution Architect in Financial Services (banking, superannuation, insurance, etc.) and expertise in customer data architecture . Proficiency in data architecture , data modeling , data warehouses , data lake design , and advanced analytics platforms . Experience in data transformation logic , data ingestion patterns , and data quality frameworks . Expertise in documenting and aligning business data requirements with technical solutions. Strategic thinker with strong collaboration and leadership capabilities. Excellent communication skills , translating business objectives into scalable data solutions. Project and stakeholder management , ensuring architectural deliverables are on track. Proven ability to manage multiple concurrent data architecture initiatives . Specific Skills We Are Seeking Candidates to Possess and Demonstrate Are: Ability to lead and operate independently , while collaborating with business users, architects, data engineers, testers, and analysts. Strong understanding of business workflows, enterprise systems , and gathering technical and business data requirements . Proficiency in creating data architecture artifacts , including ERDs, interface specs, data dictionaries, transformation logic, and lineage diagrams . Hands-on experience with complex SQL , ETL pipelines , and cloud-based data platforms . Additionally, It Would Be Advantageous If Candidates Can: Develop Power BI semantic models and design visual analytics dashboards for key business metrics. Evaluate and optimize data warehouse architecture and cloud migration strategies . Create data quality frameworks and reconciliation strategies across enterprise data sources. Lead or contribute to data governance initiatives and architectural enhancements.

Role & responsibilities Design and develop conceptual, logical, and physical data models for enterprise and application-level databases. Translate business requirements into well-structured data models that support analytics, reporting, and operational systems. Define and maintain data standards, naming conventions, and metadata for consistency across systems. Collaborate with data architects, engineers, and analysts to implement models into databases and data warehouses/lakes. Analyze existing data systems and provide recommendations for optimization, refactoring, and improvements. Create entity relationship diagrams (ERDs) and data flow diagrams to document data structures and relationships. Support data governance initiatives including data lineage, quality, and cataloging. Review and validate data models with business and technical stakeholders. Provide guidance on normalization, denormalization, and performance tuning of database designs. Ensure models comply with organizational data policies, security, and regulatory requirements. Looking for a Data Modeler Architect to design conceptual, logical, and physical data models. Must translate business needs into scalable models for analytics and operational systems. Strong in normalization , denormalization , ERDs , and data governance practices. Experience in star/snowflake schemas and medallion architecture preferred. Role requires close collaboration with architects, engineers, and analysts. Data modelling, Normalization, Denormalization, Star and snowflake schemas, Medallion architecture, ERDLogical data model, Physical data model & Conceptual data model

Design and develop conceptual, logical, and physical data models for enterprise and application-level databases. Translate business requirements into well-structured data models that support analytics, reporting, and operational systems. Define and maintain data standards, naming conventions, and metadata for consistency across systems. Collaborate with data architects, engineers, and analysts to implement models into databases and data warehouses/lakes. Analyze existing data systems and provide recommendations for optimization, refactoring, and improvements. Create entity relationship diagrams (ERDs) and data flow diagrams to document data structures and relationships. Support data governance initiatives including data lineage, quality, and cataloging. Review and validate data models with business and technical stakeholders. Provide guidance on normalization, denormalization, and performance tuning of database designs. Ensure models comply with organizational data policies, security, and regulatory requirements.

Design and develop conceptual, logical, and physical data models for enterprise and application-level databases. Translate business requirements into well-structured data models that support analytics, reporting, and operational systems. Define and maintain data standards, naming conventions, and metadata for consistency across systems. Collaborate with data architects, engineers, and analysts to implement models into databases and data warehouses/lakes. Analyze existing data systems and provide recommendations for optimization, refactoring, and improvements. Create entity relationship diagrams (ERDs) and data flow diagrams to document data structures and relationships. Support data governance initiatives including data lineage, quality, and cataloging. Review and validate data models with business and technical stakeholders. Provide guidance on normalization, denormalization, and performance tuning of database designs. Ensure models comply with organizational data policies, security, and regulatory requirements.