{"id":3955262,"url":"https://alion.io/job/proarch-data-platform-architect","title":"Data Platform Architect","company":{"id":6421,"name":"ProArch","domain":"proarch.com","url":"https://alion.io/company/proarch","size_band":"201-500","is_staffing_agency":false,"employer_type":"services","is_intermediary":false,"listed_via":null,"ats_vendor":"Workable","truth_index":null},"role":"Data Science","role_family":"Data Science","seniority":"staff","employment_type":"contractor","work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"board_field","remote_working_hours":null,"hiring_geo_confidence":"structured","locations":[],"countries":[],"hiring_countries":["IN"],"hiring_countries_total":1,"salary":null,"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agile","optional":false},{"name":"Azure","optional":false},{"name":"CI/CD","optional":false},{"name":"Databricks","optional":false},{"name":"ETL/ELT","optional":false},{"name":"FinOps","optional":false},{"name":"GCP","optional":false},{"name":"Matillion","optional":false},{"name":"Oracle","optional":false},{"name":"PostgreSQL","optional":false},{"name":"Python","optional":false},{"name":"ServiceNow","optional":false},{"name":"Snowflake","optional":false},{"name":"SQL","optional":false},{"name":"Waterfall","optional":false}],"status":"live","first_seen_at":"2026-11-09T07:29:44Z","employer_posted_date":"2026-11-09","last_verified_at":"2026-11-09T07:29:44Z","board_verified":true,"closed_at":null,"days_open":0,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":0},"description":"ESSENTIAL JOB FUNCTIONS:\nLead the definition and evolution of the enterprise data platform strategy by developing, maintaining, and continuously evolving architecture standards, reference architectures, and design patterns aligned with business priorities, analytical requirements, and AI/ML enablement across data and ETL/ELT platforms.\nDevelop, maintain, and steward enterprise architecture artifacts and documentation-including current and target state designs, diagrams, standards, and decision records-ensuring accuracy, consistency, and accessibility within the architecture repository.\nEvaluate, recommend, and govern the selection of data platforms and ETL/ELT tools, balancing scalability, performance, security, cost, and operational maturity while reducing unnecessary platform sprawl.\nReview and guide data platform and pipeline designs to ensure consistency with enterprise standards, scalability requirements, and architectural best practices.\nProvide technical leadership and guidance to data engineering teams, analytics teams, platform product owners to translate architecture standards into implementable solutions and influence technical direction across the organization.\nDefine architectural guardrails that ensure data platforms can scale reliably, meet performance expectations, and support high availability and disaster recovery requirements.\nEstablish architectural standards for platform operations, environment management, reliability, observability, deployment automation, and lifecycle management to ensure data platforms are production-ready and supportable.\nEnsure data platform architectures incorporate security controls, data privacy requirements, and regulatory compliance (e.g., access controls, encryption, data lineage, and retention) by default.\nDefine and standardize ETL/ELT and data integration patterns, including batch, streaming, and event driven approaches, to support analytics, operational reporting, and downstream consumption.\nParticipate in enterprise architecture governance forums, providing clear architectural guidance and decision support for data platform and integration initiatives.\nIncorporate financial discipline into platform architecture by guiding cost efficient design, platform right sizing, and lifecycle management in partnership with FinOps and platform teams.\nContinuously assess emerging data platform and ETL technologies, recommending updates to standards and strategy as capabilities and business needs evolve.\nDrive innovation in AI-powered data engineering workflows and automation.\nPerform other duties as assigned.\nRequirements\nBachelor’s degree in Information Technology, Data Science, Computer Science, or related field; or an equivalent combination of education and experience.\n7+ years in database engineering with 3+ years in database architecture design and support.\nPreferred Education, Additional Qualifications and Experience\nMaster’s degree in Information Technology, Data Science, Systems Engineering, or Computer Science\nFamiliarity with healthcare payer data domains such as claims, eligibility, provider, member, care management, utilization management, or regulatory reporting.\nExperience designing API-based data integration using Apigee\nIntegration with enterprise systems including Salesforce, FACETS, and ServiceNow\nRequired Knowledge, Skills, and/or Abilities\nExperience architecting enterprise data platforms across cloud environments (Azure, Google Cloud).\nDeep knowledge of Snowflake as an enterprise data warehouse platform.\nHands-on familiarity with modern data platforms and services (e.g. Azure Data Lake/ADLS, Fabric, Databricks, SQL Server, PostgreSQL, Oracle).\nHands-on experience with ETL/ELT orchestration platforms (Matillion).\nStrong hands-on technical fluency with SQL and Python sufficient to prototype, review optimize, and guide engineering implementation of data pipelines and transformations.\nAbility to design analytics-ready datasets that support reporting, operational analytics, and AI/ML use cases.\nExperience with data architecture patterns, including layered architectures (ingestion, transformation, repository, consumption).\nExperience with data modeling, analytics platforms, and data governance concepts.\nAbility to design data platforms with security controls by default, including access controls, encryption, data lineage, and retention.\nExperience integrating internal and external data sources using secure, governed ingestion methods.\nAbility to translate architectural standards into implementable solutions with engineering teams.\nExperience enabling AI/ML workloads through scalable, well-governed data platforms.\nFamiliarity with infrastructure-as-code concepts, automation, and CI/CD for data platforms.\nUnderstanding of observability, reliability, and operational readiness for data pipelines and platforms.\nAbility to evaluate emerging data technologies and recommend adoption based on maturity, risk, and business value.\nCommunicate complex technical concepts to engineering with good diagramming hygiene for mutual understanding.\nProficient communication and presentation skills for inter-level audiences.\nComfortable in agile or waterfall methodologies.","description_format":"text","description_chars":5200,"description_truncated":false,"requirements":{"experience_years_min":null,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"bachelor","optional":false},"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[{"name":"India","iso":"IN","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":["Managed Security","IT Consulting & Digital Transformation","AI Consulting & Integration"],"lifecycle":[{"event":"open","at":"2026-11-09T07:29:44Z"}],"visa":[],"liveness":{"score":86,"band":"hot","label":"Hiring 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