Snowflake Technical Lead - Financial Applications

Job Details

• Job Title: Snowflake Technical Lead - Financial Applications
• Location: Bangalore / Chennai (Onsite / Hybrid)
• Experience: 8-12+ Years
• Employment Type: Full-Time / Long-Term Engagement
• Domain: Financial Services / Private Equity / Investment Management

Job Summary

We are seeking an experienced and hands-on Snowflake Technical Lead to lead the design, development, integration, optimization, and production support of enterprise data solutions supporting financial applications.

The ideal candidate will combine deep expertise in Snowflake, SQL, data engineering, ETL/ELT and cloud data platforms with strong functional and technical understanding of financial-services applications and their underlying data.

This is a hands-on technical leadership role requiring the individual to architect solutions, develop complex data pipelines, troubleshoot production issues, perform technical reviews, and mentor engineering teams.

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.

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, Dynamic 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.

Required Technical Skills

• 8-12+ years of overall experience in database, data engineering, BI or enterprise data platforms.
• Minimum 4+ years of strong hands-on Snowflake experience.
• Expert-level SQL skills including complex queries, performance tuning and troubleshooting.
• Strong experience with Snowflake architecture, data modeling and workload optimization.
• Strong ETL/ELT and enterprise data-integration experience.
• Experience with Python or equivalent scripting/programming technologies for data engineering.
• Experience implementing automated data-quality and reconciliation controls.
• Experience with cloud platforms such as Azure or AWS.
• Experience with CI/CD, Git and automated deployment practices for data platforms.
• Strong understanding of data security, governance and access-control principles.

Mandatory Financial Application Experience

• Direct hands-on Investran experience is mandatory.
• Strong understanding of Investran database/data structures, financial data and integration patterns.
• Experience extracting, transforming, reconciling or reporting Investran data.
• Strong understanding of Private Equity / Alternative Investments / Investment Management data.
• Understanding of financial concepts including funds, investors, investments, commitments, capital calls, distributions and transactions.
• Ability to communicate effectively with both financial-domain stakeholders and technical engineering teams.

Preferred Skills

• Experience with other investment-management or financial platforms in addition to Investran.