Sr. Software Engineer - SnowFlake Job at Yash Technologies

Bangalore, karnataka, India -

Full Time

Start Date

Immediate

Expiry Date

11 Sep, 26

Salary

0.0

Posted On

13 Jun, 26

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Snowflake Architecture, Snow SQL, Snowpipe, Data Engineering, RBAC, Performance Tuning, PySpark, SQL, Data Governance, Data Replication, Snowpark, ETL Processes

Industry

IT Services and IT Consulting

Description

YASH Technologies is a leading technology integrator specializing in helping clients reimagine operating models, enhance competitiveness, optimize costs, foster exceptional stakeholder experiences, and drive business transformation. At YASH, we’re a cluster of the brightest stars working with cutting-edge technologies. Our purpose is anchored in a single truth – bringing real positive changes in an increasingly virtual world and it drives us beyond generational gaps and disruptions of the future. We are looking forward to hire SnowFlake Professionals in the following areas : Job Description: Experience required: 3-5 years. Snowflake Architecture and Administration: Demonstrate a deep understanding of Snowflake architecture, including compute and storage management. Illustrate the administrative tasks involved in managing Snowflake accounts, optimizing performance, and ensuring fail-safe operations. Snowflake Utilities and Features: Hands-on experience with Snowflake utilities, such as Snow SQL, Snow pipe, and time travel, is essential. Proficiency in writing stored procedures, using Snowflake functions, and managing tasks will be required. Data Engineering Expertise: Exhibit expertise in engineering platform components like data pipelines, data masking, data orchestration, data quality, data governance, and analytics within the Snowflake environment. Load Operations and Performance: Review and implement Snowflake best practices for managing load operations and optimizing performance to ensure efficient data processing. Data Security and Governance: Describe data governance in Snowflake, including the use of secure views and dynamic data masking features for column-level data security. Design and develop secure access to objects using Role-Based Access Control (RBAC). Data Sharing and Replication: Utilize data replication for sharing data across accounts securely and managing failover scenarios. Large-Scale Data Intelligence: Demonstrate hands-on experience in implementing large-scale data intelligence solutions around Snowflake data warehousing. Knowledge of scripting languages like Spark, Py-Spark, Snowpark, or SQL is highly desirable. Performance Tuning: Implement advanced techniques for performance tuning methodologies in Snowflake to optimize query performance and reduce data processing time. Collaboration and Leadership: Work collaboratively with cross-functional teams to understand data requirements and contribute to the data engineering strategy. Provide technical leadership and mentorship to junior team members. Strategic Impact Impacts the effectiveness of own works team through the quality and timeliness of the work produced. Largely works within standardized procedures and practices to achieve objectives and meet deadlines and gains some discretion in problem solving. Scope of People Responsibility Manages own workload effectively and efficiently. Expands technical contribution and encourage knowledge management and promote the cross-fertilization of ideas and information between teams. Foster Snowflakes & other developers to grow and mentor to help ensure overall solutions are delivered on timely manner. Provides training for members of the team and ensures team effectiveness. May provide informal guidance and support to colleagues with less experience. Cooperation Communicates difficult concepts and negotiates with others to adopt a different viewpoint. Fostering accountability throughout the team to uphold strong governance in the form of standards, methodology and requirements. Demonstrates the ability to work as a team member on a project and can effectively work with a larger global team.|h2. | Candidate’s Profile Work Experience Overall 3-5 years of experience in IT Bachelor's or master's degree in computer science, Information Technology, or a related field. Extensive experience working with Snowflake data warehousing technology, including hands-on experience with various Snowflake utilities and features. Proficiency in SQL and scripting languages such as Spark, PySpark, Python or Snowpark. Strong knowledge of data engineering concepts, data integration, and ETL processes. Familiarity with data governance principles, data security, and RBAC. Excellent understanding of data replication and data sharing across accounts. Proven experience in performance tuning and optimization of Snowflake queries. Exceptional problem-solving skills and ability to address complex data engineering challenges. Excellent communication and leadership skills with a collaborative mindset. Ability to manage multiple accounts across the organization and ensure smooth operations. Knowledge of transaction and concurrency models, DDL operations, and DML considerations in Snowflake. At YASH, you are empowered to create a career that will take you to where you want to go while working in an inclusive team environment. We leverage career-oriented skilling models and optimize our collective intelligence aided with technology for continuous learning, unlearning, and relearning at a rapid pace and scale. Our Hyperlearning workplace is grounded upon four principles Flexible work arrangements, Free spirit, and emotional positivity Agile self-determination, trust, transparency, and open collaboration All Support needed for the realization of business goals, Stable employment with a great atmosphere and ethical corporate culture

Responsibilities

Design and manage Snowflake architecture, including compute, storage, and data pipelines to ensure efficient data processing. Provide technical leadership and mentorship to junior team members while collaborating with cross-functional teams on data engineering strategies.