Principal Consultant

Job description - Principal Consultant Snowflake/Big Data/Cloud Tech Lead:

Technical Leadership:

1. Very good at Architecting and designing complex data solutions on Snowflake, Data Sharing, Data Exchange, Snowflake Internal Marketplace, including data models, data ingestion pipelines, and data transformations, ensuring best practices and scalability.
2. Good at Snowflake internals for any customization using Configuration changes- For example, customizing the Dashboard content on the Snowflake Internal Marketplace
3. Good at Architecture principles and work with Enterprise Architect for executing Architecture strategies.
4. Good at building solutions on Big data and Custom catalogues for Data collaboration.
5. Good at Cloud-native Application/Big Data principles and experience in building Cloud-native data solutions using AWS/Azure cloud stack.
6. Good at building Bid data principles & solutions on MS Fabric/OneLake or similar platforms.
7. Experience in building solutions for Data products ecossystem and Data Collaboration platforms.
8. Good at understanding Open data formats like Iceberg and delta for specific Investment banking use cases.
9. Good at integrating Snowflake data platform with Non-snowflake clients and vice-versa
10. Expertise in building Data Engineering projects' lifecycle.
11. Preferable with experience in building Data Mesh and Data Products, publishing/consuming data products on Marketplace using Snowflake or AWS or Azure.
12. Good at using AWS stack using S3, Glue, Lambda, Snowflake platform on AWS, Redshift and Glue catalog.
13. Preferable in using Azure stack like ADLS2.0, ADF2.0, Synapse.
14. Very good at Programming in Python and Pyspark, Java, Notebook development using VSCode and performance improvement practices.
15. Good at building projects using SAFe Agile practices.
16. Good at writing technical documents like High-level Solution Design and Detailed Design for Big data/cloud based projects.

Data Modeling:

1. Designing data structures and optimizing data organization within Snowflake to support efficient querying and analysis.
2. Designing standard Datawarehouse models using Star schema and Data Valut practices and support SCD-2 scenarios.

Data Integration:

Implementing ETL/ELT processes to integrate data from various sources into Snowflake and MS Fabric/OneLake, ensuring data quality and consistency.

Team Management:

Leading and mentoring a team of engineers on Snowflake development, providing technical guidance, code reviews, and problem-solving support.

Performance Optimization:

1. Monitoring and optimizing Snowflake queries, data loading strategies, and warehouse configurations to maximize performance.
2. Performance code reviews in Data pipeline code, Snowflake Query tuning techniques and good at resolving Snowflake Data Scalability and Size issues.

Team level Collaboration:

Working closely with cross-functional teams like business analysts, product managers, and data scientists to understand data requirements and translate them into technical solutions.

Compliance, Regulatory and Security:

Implementing data security measures within Snowflake to protect sensitive data, adhering to industry regulations and compliance standards.

Cloud-based CI/CD development and Management:

1. Setting up and maintaining continuous integration and continuous delivery pipelines for Snowflake applications.
2. Preferable with experience in the AWS or Azure DevOps and Snowflake solutions.

Troubleshooting and Support:

Identifying and resolving complex technical issues related to Snowflake data processing, performance and operations.

Personal excellence:

1. Excellent communication and collaboration skills to work with diverse teams.
2. Proven ability to lead technical projects and mentor junior engineers.
3. Good at concept articulation skills and concept realization through POCs.
4. Good at shaping the product backlog based on Business requirements/asks.