Senior Data Engineer - R01572077

Brillio 2
Pune +1 more
Hybrid

Who this role is best for

Geared toward data engineers comfortable with advanced SQL and AI-powered data processing, and based in Pune, India, with a focus on Snowflake engineering and collaboration across data and business teams.

Best fit for

  • Candidates with 2-4 years of Snowflake engineering experience and advanced SQL development background
    — “2 to 4 years of hands-on experience in Snowflake engineering and advanced SQL development”
  • Professionals who have implemented generative AI use cases in Snowflake
    — “Experience implementing generative AI use cases such as semantic search or information extraction in Snowflake”
  • Individuals who can optimize Snowflake workloads for performance and cost efficiency
    — “Optimize SQL queries and Snowflake workloads for enhanced performance and reduced cost”

Things to consider

  • Certifications like SnowPro Core and SQL are preferred but not explicitly required
    — “Snowflake SnowPro Core Certification”

How to stand out

  • Highlight experience with Snowflake Cortex AI functions in your resume and interview responses
    — “Leverage Snowflake Cortex AI Functions such as AI_COMPLETE, AI_CLASSIFY, AI_EXTRACT, AI_SENTIMENT, AI_EMBED, and AI_SUMMARIZE_AGG”
  • Showcase your ability to work with structured and unstructured data in Snowflake
    — “Work with structured and unstructured data in Snowflake”
  • Emphasize your track record in data validation and troubleshooting
    — “Perform rigorous data validation, quality checks, and troubleshooting”
  • Demonstrate your understanding of data warehousing and Snowflake architecture
    — “Strong understanding of Snowflake architecture and data warehousing concepts”
  • Include examples of data transformation within Snowflake in your portfolio or resume
    — “Experience with data transformation techniques within Snowflake”
Pace · Fast PacedCollaboration · MediumAutonomy · MediumDecision Impact · Team

Derived from job-description analysis by Serendipath's career intelligence engine.

What success looks like

  • Developed complex SQL queries and data transformations
  • Implemented AI-powered data processing solutions
  • Optimized Snowflake workloads for enhanced performance
Typical background
2 to 4 years of hands-on experience in Snowflake engineering and advanced SQL development

Skills & requirements

Required

Snowflake EngineeringAdvanced SQLETL FundamentalsDatastreamData WarehousingSnowpipeSnowsqlTime Travel And Fail SafePlsqlT-sqlStored ProceduresData Transformation TechniquesData ValidationTroubleshootingSnowflake Cortex AI Functions

Preferred

Generative AI Use CasesOptimizing Snowflake WorkloadsData Security And GovernanceCertification In Snowflake Or Cloud Data Engineering

Stack & domain

DatastreamETL FundamentalsSQLPythonData WarehousingTime Travel And Fail SafeSnowpipeSnowsqlModern Data Platform FundamentalsPlsqlT-sqlStored ProceduresSnowflake EngineeringSnowflake Cortex AI Functions

About the role

Original posting from Brillio 2 via Lever

Senior Data Engineer

Primary Skills:

  • DataStream, ETL Fundamentals, SQL, SQL (Basic + Advanced), Python, Data Warehousing, Time Travel and Fail Safe, Snowpipe, SnowSQL, Modern Data Platform Fundamentals, PLSQL, T-SQL, Stored Procedures

Specialization:

  • Snowflake Engineering: Data Engineer

Job requirements:

  • Experience Range: 2 to 4 years of hands-on experience in Snowflake engineering and advanced SQL development Key Responsibilities: 1. Develop complex SQL queries, joins, common table expressions (CTEs), views, stored procedures, and data transformations within Snowflake 2. Leverage Snowflake Cortex AI Functions such as AI_COMPLETE, AI_CLASSIFY, AI_EXTRACT, AI_SENTIMENT, AI_EMBED, and AI_SUMMARIZE_AGG to build AI-powered data processing and analytics solutions 3. Work with structured and unstructured data in Snowflake, ensuring efficient data ingestion, transformation, and management 4. Perform rigorous data validation, quality checks, and troubleshooting to maintain data integrity and reliability 5. Optimize SQL queries and Snowflake workloads for enhanced performance and reduced cost 6. Support development and deployment of Generative AI use cases, including summarization, classification, information extraction, and semantic search 7. Collaborate with data engineers, analysts, and business teams to gather requirements and deliver tailored Snowflake solutions Required Skills: 1. Advanced SQL skills, including joins, CTEs, views, and stored procedures 2. Strong understanding of Snowflake architecture and data warehousing concepts 3. Experience with Snowflake Cortex AI Functions 4. Knowledge of data transformation techniques within Snowflake 5. Ability to work with structured and unstructured data in Snowflake Preferred Skills: 1. Experience implementing generative AI use cases such as semantic search or information extraction in Snowflake 2. Familiarity with optimizing Snowflake workloads for analytics 3. Knowledge of data security and governance in cloud data platforms 4. Certification in Snowflake or cloud data engineering Desired Qualifications: 1. Bachelor's degree in Computer Science, Information Technology, Engineering, or a closely related discipline 2. Snowflake SnowPro Core Certification 3. Relevant certification in SQL (e.g., Microsoft Certified: SQL Database Specialist)

Source: Brillio 2 careers (Lever)

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