Key Responsibilities Snowflake Architecture & Technical Leadership • Lead architecture, design and implementation of enterprise-scale Snowflake data solutions. • Define scalable data architecture covering ingestion, transformation, storage, consumption and archival. • Design appropriate databases, schemas, tables, views, secure views, stages and data-sharing mechanisms. • Establish engineering standards for Snowflake development, deployment, security and performance. • Perform technical design and code reviews and mentor Snowflake/data engineering team members. • Remain hands-on and independently troubleshoot complex production and data issues. Investran & Financial Applications Mandatory • Work directly with Investran data, databases, interfaces and downstream reporting/data platforms. • Understand Investran data structures supporting private equity, fund accounting and investment-management processes. • Analyze and map Investran data into enterprise Snowflake models. • Develop and support pipelines extracting and transforming data from Investran into Snowflake. • Understand financial entities and relationships including funds, investments, investors, commitments, capital calls, distributions, transactions, valuations and accounting data. • Reconcile source financial information against Snowflake and downstream reporting systems. • Work with Finance, Operations, Investment and Technology stakeholders to translate financial requirements into technical data solutions. • Support integration with other financial applications and enterprise data sources. Candidates without direct Investran experience should not be considered for this position. Data Engineering & ETL/ELT • Design and develop robust ETL/ELT pipelines for structured and semi-structured financial data.



• Develop complex SQL transformations, stored procedures, views and reusable data components. • Implement Snowflake capabilities including Streams, Tasks, Snowpipe, Energetic Tables and Time Travel, where appropriate. • Build batch and near-real-time ingestion patterns. • Design data models supporting operational reporting, analytics and downstream applications. • Implement automated data-quality validation, reconciliation, exception handling and audit controls. Performance & Cost Optimization • Optimize complex Snowflake queries and workloads. • Analyze query profiles and identify performance bottlenecks. • Optimize warehouse sizing, clustering, caching and compute utilization. • Establish monitoring for Snowflake performance, consumption and cost. • Recommend architectural improvements to improve scalability while controlling cloud expenditure. Integration & Analytics • Integrate Snowflake with financial applications, APIs, databases, files and cloud services. • Support BI and analytics platforms such as Power BI and Tableau. • Develop curated datasets and semantic/data consumption layers for financial reporting. • Support APIs and downstream applications consuming Snowflake data. • Collaborate with application, data, cloud, security and business teams on end-to-end solutions. Security, Governance & Production Support • Implement Snowflake RBAC, least-privilege access, masking policies, row-level security and secure data sharing. • Ensure appropriate protection of confidential financial and investor information. • Support data lineage, governance, auditability and regulatory requirements. • Lead troubleshooting of production incidents involving Snowflake, pipelines, integrations and data-quality issues. • Conduct root-cause analysis and implement permanent corrective actions.

📌 Snowflake Techincal Lead - Financial Applications (Investran) (Bengaluru)
🏢 Knowledge Artisans
📍 Bengaluru