{"id":3332717,"url":"https://alion.io/job/inumellas-consultancy-services-data-architect-snowflake-db","title":"Data Architect - Snowflake DB","company":{"id":3801175,"name":"Inumellas Consultancy Services","domain":"inumellas.com","url":"https://alion.io/company/inumellas-consultancy-services","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":null,"truth_index":null},"role":"Data Science","role_family":"Data Science","seniority":"staff","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Hyderabad, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":28000,"max_usd":53000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":17},"experience_years_min":11,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"CI/CD","optional":false},{"name":"Databricks","optional":false},{"name":"Dimensional Modeling","optional":false},{"name":"ETL/ELT","optional":false},{"name":"GCP","optional":false},{"name":"Power BI","optional":false},{"name":"pySpark","optional":false},{"name":"Python","optional":false},{"name":"Snowflake","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false},{"name":"Tableau","optional":false},{"name":"Apache Kafka","optional":true},{"name":"AWS Glue","optional":true},{"name":"Azure Data Factory","optional":true},{"name":"Microsoft Fabric","optional":true}],"status":"live","first_seen_at":"2026-10-27T12:06:08Z","employer_posted_date":null,"last_verified_at":"2026-10-27T12:06:08Z","board_verified":false,"closed_at":null,"days_open":3,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":3},"description":"Role Overview:\n\nWe are looking for an experienced Data Architect with strong expertise in Snowflake, modern cloud data platforms, and Business Intelligence (BI). The ideal candidate will own end-to-end data architecture, design scalable data engineering and analytics solutions, and translate complex business requirements into reliable, high-performance data platforms. The role requires a combination of hands-on technical architecture, BI and semantic modelling expertise, stakeholder management, and technical leadership.\n\nKey Responsibilities:\n\n1. Data Architecture & Platform Design:\n\n- Define end-to-end enterprise data architecture, including modern data warehouses, data lakes, and Lakehouse platforms.\n\n- Design scalable, secure, and cost-effective data solutions using Snowflake and/or Databricks.\n\n- Establish data modeling standards, architecture principles, integration patterns, and technology best practices.\n\n- Design data platforms using Medallion Architecture (Bronze, Silver, Gold), dimensional modelling, and enterprise data models.\n\n- Evaluate technology choices and recommend suitable architectural solutions based on business and technical requirements.\n\n2. Snowflake & Data Engineering:\n\n- Architect data ingestion, transformation, and processing pipelines using SQL, Python, Spark, and relevant cloud-native services.\n\n- Design ELT/ETL frameworks and orchestrate data workflows across multiple enterprise systems.\n\n- Optimize query performance, compute utilization, storage, scalability, and platform costs.\n\n- Define approaches for batch and real-time/streaming data processing where required.\n\n- Establish engineering standards for reusable pipelines, testing, monitoring, CI/CD, and deployment.\n\n3. Business Intelligence & Analytics:\n\n- Design enterprise BI architecture, reporting frameworks, and self-service analytics solutions.\n\n- Strong expertise in at least one BI platform, such as Power BI, Tableau, or Qlik.\n\n- Define semantic models, dimensional models, metrics, KPIs, and business calculation standards.\n\n- Establish governed datasets, reusable business measures, and consistent reporting definitions across business functions.\n\n- Optimize BI performance, dashboard responsiveness, data refresh, and large-scale reporting workloads.\n\n- Partner with business stakeholders to translate analytical requirements into actionable insights and reporting solutions.\n\n4. Data Governance, Quality & Security:\n\n- Define data governance, data quality, metadata management, lineage, and master/reference data standards.\n\n- Implement appropriate data access controls, role-based security, masking, encryption, and compliance controls.\n\n- Establish data validation and reconciliation frameworks to ensure accuracy, consistency, and reliability.\n\n- Promote trusted, discoverable, and reusable enterprise data assets.\n\n5. Technical Leadership & Stakeholder Management:\n\n- Lead architecture discussions, technical design reviews, and solution walkthroughs.\n\n- Work closely with business leaders, product owners, data engineers, BI developers, and cloud teams.\n\n- Mentor engineering teams and establish coding, modeling, documentation, and architecture best practices.\n\n- Support presales activities, solution proposals, effort estimation, and technical presentations where required.\n\n- Evaluate emerging technologies and identify opportunities to integrate AI/GenAI into data and analytics platforms.\n\nRequired Skills & Experience:\n\n- 10 - 15+ years of experience in data engineering, data architecture, data warehousing, and analytics.\n\n- Strong hands-on architecture expertise in Snowflake.\n\n- Excellent SQL skills and experience with Python, PySpark, or equivalent data processing technologies.\n\n- Strong understanding of cloud platforms such as Azure, AWS, or GCP.\n\n- Expertise in data modeling, dimensional modeling, data warehousing, lakehouse architecture, and ETL/ETL patterns.\n\n- Strong BI expertise in Power BI, Tableau, or Qlik, including semantic modeling, KPI design, and performance optimization.\n\n- Experience designing and implementing enterprise-scale data platforms and integrating data from multiple source systems.\n\n- Knowledge of data governance, security, data quality, lineage, and CI/CD practices.\n\n- Strong communication, analytical, problem-solving, and stakeholder management skills.\n\nPreferred Qualifications:\n\n- Experience with DBT, Databricks Unity Catalog, Snowflake governance features, or comparable data management capabilities.\n\n- Knowledge of Microsoft Fabric, Azure Data Factory, AWS Glue, or similar data integration services.\n\n- Exposure to streaming technologies such as Kafka or cloud-native streaming services.\n\n- Experience with AI/ML platforms, GenAI-enabled analytics, or natural-language interfaces for BI.\n\n- Relevant Snowflake, Databricks, cloud, or BI certifications.\nSkills\nData Warehousing, Python, PySpark, ETL, Snowflake DB, Data Architect, Business Intelligence, Data Ingestion, Data Governance, Data Modeling","description_format":"text","description_chars":4985,"description_truncated":false,"requirements":{"experience_years_min":11,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["IT Consulting & Digital Transformation","Enterprise Apps Implementation Partners"],"lifecycle":[{"event":"open","at":"2026-10-27T12:29:15Z"}],"visa":[],"liveness":{"score":86,"band":"hot","label":"Hiring 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