Data Platform Architect

🔥 0 minutes ago

🇮🇳 India – Remote

💵 ₹4M - ₹4.5M / year

⏳ Contract/Temporary

🟠 Senior

🔴 Lead

🔙 Backend Engineer

👻 Ghost score 0%

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ProArch

WebsiteLinkedInAll Job Openings

201 - 500 employees

💼 Consulting

🏥 Healthcare

🏭 Manufacturing

Consulting • Healthcare • Manufacturing

ProArch is a technology company that specializes in providing digital engineering, cloud services, data and AI solutions, and cybersecurity measures. They help businesses unleash their full potential by modernizing operations, protecting assets, and delivering data-driven insights. ProArch works closely with clients to eliminate roadblocks to growth and aligns advanced technology solutions with business goals to empower organizational success. As an award-winning Microsoft Gold Partner, they offer a wide range of services including AI consulting, software development, quality assurance, infrastructure management, governance, risk, and compliance solutions, and operational technology services. Their expertise extends to industries such as credit unions, power generation, and manufacturing, providing tailored solutions to meet each sector's unique challenges.

📋 Description

• Lead the definition and evolution of the enterprise data platform strategy, architecture standards, reference architectures, and design patterns aligned with business priorities, analytical requirements, and AI/ML enablement. • Develop, maintain, and steward enterprise architecture artifacts and documentation, including current and target state designs, diagrams, standards, and decision records. • Evaluate, recommend, and govern data platforms and ETL/ELT tools based on scalability, performance, security, cost, and operational maturity. • Review and guide data platform and pipeline designs for enterprise standards, scalability, and architectural best practices. • Provide technical leadership to data engineering teams, analytics teams, and platform product owners. • Define architectural guardrails for scalability, performance, high availability, and disaster recovery. • Establish standards for platform operations, environment management, reliability, observability, deployment automation, and lifecycle management. • Ensure security controls, data privacy, and regulatory compliance are incorporated into data platform architectures. • Define and standardize batch, streaming, and event-driven ETL/ELT and data integration patterns. • Participate in enterprise architecture governance forums and provide architectural guidance and decision support. • Guide cost-efficient design, platform right-sizing, and lifecycle management with FinOps and platform teams. • Assess emerging data platform and ETL technologies and recommend updates to standards and strategy. • Drive innovation in AI-powered data engineering workflows and automation. • Perform other duties as assigned.

🎯 Requirements

• Bachelor’s degree in Information Technology, Data Science, Computer Science, or related field; or an equivalent combination of education and experience. • 7+ years in database engineering with 3+ years in database architecture design and support. • Familiarity with healthcare payer data domains such as claims, eligibility, provider, member, care management, utilization management, or regulatory reporting. • Experience designing API‑based data integration using Apigee. • Integration with enterprise systems including Salesforce, FACETS, and ServiceNow. • Experience architecting enterprise data platforms across cloud environments (Azure, Google Cloud). • Deep knowledge of Snowflake as an enterprise data warehouse platform. • Hands-on familiarity with modern data platforms and services (e.g. Azure Data Lake/ADLS, Fabric, Databricks, SQL Server, PostgreSQL, Oracle). • Hands‑on experience with ETL/ELT orchestration platforms (Matillion). • Strong hands‑on technical fluency with SQL and Python sufficient to prototype, review, optimize, and guide engineering implementation of data pipelines and transformations. • Ability to design analytics‑ready datasets supporting reporting, operational analytics, and AI/ML use cases. • Experience with data architecture patterns, including layered architectures (ingestion, transformation, repository, consumption). • Experience with data modeling, analytics platforms, and data governance concepts. • Ability to design data platforms with security controls by default, including access controls, encryption, data lineage, and retention. • Experience integrating internal and external data sources using secure, governed ingestion methods. • Ability to translate architectural standards into implementable solutions with engineering teams. • Experience enabling AI/ML workloads through scalable, well‑governed data platforms. • Familiarity with infrastructure-as-code concepts, automation, and CI/CD for data platforms. • Understanding of observability, reliability, and operational readiness for data pipelines and platforms. • Ability to evaluate emerging data technologies and recommend adoption based on maturity, risk, and business value. • Communicate complex technical concepts to engineering with good diagramming hygiene for mutual understanding. • Proficient communication and presentation skills for inter-level audiences. • Comfortable in agile or waterfall methodologies.

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