Data Platform Architect

Location: Offshore or Nearshore (Remote)

Type of Role: Contract (Staff Augmentation)

Time Zone: Must overlap with Eastern Time (EST) working hours

Overview An organization is seeking a Data Platform Architect to define, design, and govern its enterprise data platform architecture supporting analytics, operational reporting, and emerging AI/ML use cases. This role establishes architectural direction across cloud data platforms, data warehousing, and ETL/ELT integration capabilities, ensuring solutions are scalable, secure, cost-efficient, reliable, and aligned with enterprise standards and business priorities.

The Data Platform Architect will work closely with Data Platform Product Management, Data Engineering, Analytics, Cloud Engineering, Security, and Enterprise Architecture teams to translate business and data requirements into implementable technical architectures. The role provides hands-on architectural leadership, establishes reference architectures and design patterns, guides technology selection, and ensures that security, compliance, governance, reliability, and financial efficiency are built into platform design and operations. Offshore and nearshore candidates are welcome, provided they can maintain meaningful overlap with EST working hours.

Key Responsibilities

- Define and evolve the enterprise data platform architecture strategy, including architecture standards, reference architectures, and design patterns aligned with business priorities, analytics requirements, and AI/ML enablement.
- Design and govern enterprise data platforms across cloud environments, including data warehousing, data lakes, data integration, and analytics platforms.
- Evaluate, recommend, and govern data platforms and ETL/ELT technologies, balancing scalability, performance, security, cost, and operational maturity while minimizing unnecessary platform complexity.
- Establish and maintain enterprise architecture documentation, including current-state and target-state designs, architecture diagrams, technical standards, and architecture decision records.
- Review and guide data platform and pipeline designs to ensure alignment with enterprise architecture standards, scalability requirements, and technical best practices.
- Define and standardize ETL/ELT and data integration patterns, including batch processing, streaming, and event-driven integration, to support analytics, operational reporting, and downstream data consumption.
- Provide technical leadership to Data Engineering, Analytics, Cloud Engineering, and platform teams, translating architecture standards into implementable solutions and guiding technical decisions.




- Design layered data architectures covering ingestion, transformation, data repositories, and consumption to deliver analytics-ready datasets for reporting, operational analytics, and AI/ML workloads.
- Establish architectural standards for platform reliability, high availability, disaster recovery, observability, deployment automation, environment management, and lifecycle management.
- Embed security, privacy, and regulatory compliance requirements into platform architecture, including access controls, encryption, data lineage, retention, and secure data ingestion.
- Partner with Security, Risk, Compliance, and Enterprise Architecture teams to support architecture governance and ensure alignment with enterprise policies and regulatory requirements.
- Guide cost-efficient platform architecture through workload optimization, resource right-sizing, platform lifecycle management, and collaboration with FinOps and Cloud Engineering teams.
- Evaluate emerging data platform technologies, architecture patterns, and AI-powered data engineering capabilities, recommending adoption based on business value, technical maturity, and risk.
- Support automation and engineering efficiency through infrastructure-as-code concepts, CI/CD practices, and AI-enabled data engineering workflows.

Required Experience & Skills

- Bachelor’s degree in Computer Science, Information Technology, Data Science, or a related field, or an equivalent combination of education and experience.
- 7+ years of experience in database engineering, including 3+ years in database architecture design and support.
- Proven experience architecting enterprise data platforms across cloud environments, particularly Azure and Google Cloud.
- Deep knowledge of Snowflake as an enterprise data warehouse platform.
- Hands-on familiarity with modern data platforms and services, including Azure Data Lake Storage (ADLS), Microsoft Fabric, Databricks, SQL Server, PostgreSQL, and Oracle.
- Hands-on experience with ETL/ELT orchestration platforms, particularly Matillion.
- Strong technical proficiency in SQL and Python, with the ability to prototype solutions, review and optimize data pipelines, and guide engineering implementation.
- Experience designing enterprise data architectures,



including layered data processing patterns, data modeling, analytics platforms, and governed data repositories.
- Strong understanding of data integration patterns and the secure integration of internal and external data sources.
- Experience designing scalable, analytics-ready datasets that support enterprise reporting, operational analytics, and AI/ML use cases.
- Knowledge of data governance, metadata, data lineage, privacy, security controls, and regulatory compliance requirements.
- Experience defining architecture standards for reliability, performance, high availability, disaster recovery, observability, and operational readiness.
- Ability to translate business and data requirements into practical architecture designs, technical standards, and implementation guidance for engineering teams.
- Strong communication and presentation skills, including the ability to explain complex technical concepts through clear architecture diagrams and documentation.
- Ability to evaluate technology options, communicate architectural trade-offs, and influence technical decisions across multiple teams.
- Comfortable working in Agile or Waterfall delivery environments.
- Ability to collaborate with distributed teams and maintain meaningful overlap with EST working hours.

Nice to Have

- Master’s degree in Information Technology, Data Science, Systems Engineering, Computer Science, or a related field.
- Experience with healthcare payer data domains, including claims, eligibility, provider, member, care management, utilization management, or regulatory reporting.
- Experience designing API-based data integrations using Apigee.
- Experience integrating enterprise systems such as Salesforce, FACETS, and ServiceNow.
- Familiarity with infrastructure-as-code, deployment automation, and CI/CD practices for data platforms.
- Experience enabling AI/ML workloads through scalable, secure, and well-governed data architectures.
- Experience with cloud cost optimization, FinOps practices, platform right-sizing, and technology lifecycle management.
- Experience participating in enterprise architecture review boards, governance forums, or technical design reviews.
- Familiarity with emerging data engineering technologies and AI-powered automation for data platform development and operations.

Equal Prospect Statement: BigRio is an equal-opportunity employer committed to creating a diverse and inclusive workplace. We value and promote diversity and prohibit discrimination based on various factors outlined by federal, state, or local laws. All qualified applicants will receive equal consideration for employment.

📌 Data Platform Architect (India)
🏢 BigRio
📍 India