Preferred candidate profile

Core technical skills (must have)

- Snowflake: Strong knowledge of the architecture (virtual warehouses, micro-partitions, clustering, caching), Snowpipe, Streams, Tasks, Dynamic Tables, Snowpark, stored procedures, semi-structured data (VARIANT, FLATTEN), secure data sharing, performance tuning and cost management.

Experience with Snowflake Cortex is preferred.

- ELT / ETL: Solid experience designing and operating ELT/ETL pipelines and data ingestion processes using tools such as dbt, Airflow or equivalent orchestration, Cribl, Kafka, Kinesis and Fivetran. This includes incremental loading, idempotent design, scheduling, monitoring, and error handling and recovery.

- Python and SQL (PySQL): Advanced SQL (complex joins, window functions, CTEs, query optimization) and solid Python programming for data processing, automation, API integration and testing. Java and JavaScript are a plus.

- Big data: Experience with large-scale datasets, both batch and streaming, and with data warehouses, data lakes and lakehouse patterns (for example, Apache Spark, Databricks, Apache Iceberg and Parquet).

Experience with other platforms such as BigQuery, Redshift or Azure Synapse is a plus.

- AI and machine learning: Working knowledge of AI/ML and generative AI, including Snowflake Cortex AI (LLM functions, vector search, Document AI), preparing data for ML models, and using AI assistants such as Copilot, ChatGPT, Gemini or Anthropic Claude to improve engineering productivity. Awareness of responsible AI, model risk and data privacy considerations.

- Data modeling, quality and governance: Data modeling (dimensional and relational), normalization and schema design. Implementation of validation, quality checks and reconciliation. Understanding of metadata, lineage and data governance. Familiarity with standards such as OCSF and OTEL.





- Databases: Hands-on experience with relational databases (for example, SQL Server, PostgreSQL, Oracle) and exposure to NoSQL databases (for example, MongoDB, DynamoDB).

- Cloud and DevOps: Experience with at least one major cloud provider (AWS, Azure or Google), including object storage such as AWS S3, plus Git, CI/CD pipelines and infrastructure-as-code (for example, Terraform).

- Reporting and security data: Experience with reporting tools such as Power BI or Tableau. Familiarity with SIEM and log sources such as Splunk, Elastic, Datadog, AWS CloudTrail, CloudWatch and Azure Event Hub is a plus.

Cyber and IAM fundamentals (candidate must demonstrate)

- Cybersecurity basics: Understanding of the CIA triad, defense in depth, least privilege, encryption at rest and in transit, key and secrets management, network security basics, logging and monitoring, vulnerability management and incident response. Familiarity with the MITRE ATT&CK; framework and with frameworks such as NIST CSF and CRI.

- IAM basics: Understanding of authentication versus authorization, SSO and federation (SAML, OIDC, OAuth 2.0), SCIM provisioning, MFA, role-based and attribute-based access control, the joiner-mover-leaver lifecycle, privileged and service accounts, access reviews and recertification, and segregation of duties.

- IAM data awareness: Ability to explain how identity, account, entitlement and authentication data from IAM platforms (for example, SailPoint, CyberArk, Microsoft Entra ID, Ping) supports governance, control monitoring and audit. Hands-on exposure to any of these platforms is an advantage.

- Secure engineering and data protection: Secure development practices, data classification, handling of personal and sensitive personal information (masking, retention, access controls), and awareness of data privacy and banking regulatory expectations.

📌 Snowflake Engineer For IAM - AVP (Bengaluru)
🏢 Mufg Enterprise
📍 Bengaluru