{"id":3392198,"url":"https://alion.io/job/systango-technologies-limited-data-architect-snowflakedatabricks","title":"Data Architect – Snowflake/Databricks","company":{"id":450069,"name":"Systango Technologies Limited","domain":"systango.com","url":"https://alion.io/company/systango-technologies-limited","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Keka","truth_index":null},"role":"Data Science","role_family":"Data Science","seniority":"staff","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Indore, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":28000,"max_usd":52000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":17},"experience_years_min":10,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Apache Kafka","optional":false},{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"Azure Data Factory","optional":false},{"name":"CI/CD","optional":false},{"name":"Data Vault","optional":false},{"name":"Databricks","optional":false},{"name":"dbt","optional":false},{"name":"Dimensional Modeling","optional":false},{"name":"ETL/ELT","optional":false},{"name":"GCP","optional":false},{"name":"Git","optional":false},{"name":"Machine Learning","optional":false},{"name":"pySpark","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"Snowflake","optional":false},{"name":"SQL","optional":false},{"name":"Delta Lake","optional":true},{"name":"Spark","optional":true}],"status":"live","first_seen_at":"2026-10-28T08:50:31Z","employer_posted_date":"2026-10-28","last_verified_at":"2026-10-31T19:03:59Z","board_verified":true,"closed_at":null,"days_open":3,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":3},"description":"About Systango\nSystango is a technology company listed on the NSE, delivering innovative digital solutions across Generative AI, AI/ML, Data Engineering, Analytics, Blockchain/Web3, Cloud, and FinTech. We partner with global clients to build scalable, secure, and high-performance technology solutions.\nRole Overview\nWe are looking for an experienced Data Architect with strong expertise in Snowflake/Databricks to design and lead the implementation of scalable, cloud-native data platforms. The ideal candidate will combine deep technical expertise in modern data architecture with hands-on experience in data engineering, cloud ecosystems, data governance, and enterprise data strategy.\nYou will work closely with engineering teams, business stakeholders, and client-facing teams to translate business requirements into robust data architectures that support analytics, reporting, and AI/ML use cases.\nKey Responsibilities\nData Architecture: Define end-to-end data architecture, including data lakes, lakehouses, modern data warehouses, data marts, and enterprise data platforms.\nSnowflake & Databricks: Design and optimize data solutions using Snowflake OR Databricks, selecting appropriate architectural patterns based on business and technical requirements.\nData Engineering: Architect scalable batch and streaming pipelines, ETL/ELT workflows with medallion architecture, data transformations using dbt, and orchestration frameworks.\nCloud Platforms: Design data solutions on AWS, Azure, or GCP, integrating cloud storage, compute, security, and networking services.\nData Modelling: Define conceptual, logical, and physical data models, including dimensional modelling, Data Vault 2.0, and normalized data structures.\nPerformance & Cost Optimization: Optimize query performance, compute utilization, storage, workload management, and overall platform costs.\nData Governance & Security: Establish standards for data quality, lineage, metadata management, access control, encryption, privacy, and regulatory compliance.\nArchitecture Standards: Define reusable architecture patterns, engineering best practices, coding standards, CI/CD processes, and data platform design principles.\nTechnical Leadership: Mentor data engineers and technical leads, conduct architecture reviews, and guide teams through complex technical decisions.\nStakeholder Collaboration: Work with product owners, business stakeholders, and clients to understand requirements and communicate architectural decisions effectively.\nAI & Analytics Enablement: Build data foundations that support BI, advanced analytics, machine learning, and Generative AI applications, including RAG and vector search use cases where applicable.\nRequired Skills & Experience\n10-15 years of experience in data engineering, data architecture, or enterprise data platforms.\nStrong hands-on expertise in Snowflake/Databricks, including architecture, implementation, optimization, and production-scale deployments.\nExcellent proficiency in SQL and Python, with experience in PySpark and distributed data processing.\nStrong understanding of modern data architecture patterns, including lakehouse, data warehouse, data lake, and medallion architecture.\nProven experience designing enterprise-grade ETL/ELT pipelines and scalable data integration frameworks.\nExperience with cloud platforms such as AWS, Microsoft Azure, or GCP.\nStrong understanding of data modelling, dimensional modelling, Data Vault, and data warehouse design principles.\nMust have strong hands-on experience with Kafka, real-time data streaming, event-driven architectures, and high-throughput distributed data processing.\nExperience with orchestration tools such as Airflow, Azure Data Factory, or equivalent platforms.\nFamiliarity with data governance, data quality frameworks, lineage, metadata management, and enterprise security.\nExperience with Git, CI/CD, infrastructure as code, and automated data deployment practices.\nDemonstrated ability to lead architecture discussions, mentor engineers, and make sound technical decisions.\nProven experience building and mentoring Data Engineering teams, including junior engineers, through technical guidance, code reviews, and best-practice implementation.\nMust hold at least one valid Snowflake or Databricks certification.\nMust have hands-on experience designing and optimizing production data platforms processing petabytes of data.\nExcellent communication, problem-solving, and stakeholder management skills.\nGood to Have\nExperience with dbt, Delta Lake, Unity Catalog, Snowflake Dynamic Tables, or Snowpark.\nKnowledge of Kafka, Spark Structured Streaming, or other real-time data processing technologies.\nExperience with data mesh, domain-driven data architecture, or multi-tenant data platforms.\nExperience building data platforms for AI/ML, GenAI, feature engineering, and vector search.\nExposure to FinTech, payments, financial services, or other data-intensive industries.\nWhat Success Looks Like\nDesigning scalable, secure, and cost-efficient data platforms aligned with business objectives.\nEstablishing architecture standards that improve data reliability, quality, and engineering productivity.\nEnabling faster delivery of analytics, reporting, and AI-driven solutions.\nProviding technical direction and raising the overall architecture and engineering maturity of the 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