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Snowflake Data Solutions Architect

Snowflake Data Solutions Architect

Tata Consultancy ServicesHyderabad, Republic Of India, IN
30+ days ago
Job description

Role : Senior Snowflake Developer

Required Technical Skill Set :

  • Strong proficiency in SQL for Snowflake.
  • Hands-on experience with Excel data handling (e.G., VBA, macros, or scripting to clean and transform Excel data).
  • Expertise in ETL / ELT processes and tools (e.G., Talend, Informatica, Matillion, or dbt).
  • Knowledge of scripting languages like Python for data extraction and automation.
  • Familiarity with cloud platforms (AWS, Azure, or GCP) and their integration with Snowflake.
  • Performance Tuning : Ability to optimize queries and improve Snowflake performance for large datasets.

Experience : 6 to 8 years

Location : Pan India

Job Description :

Desired Competencies (Technical / Behavioral Competency)

Must-Have : -

  • Experience in migrating data from Excel or other structured file sources to Snowflake.
  • Strong analytical skills to assess data quality and ensure accuracy during migration.
  • Ability to automate recurring workflows and streamline data ingestion processes.
  • Excellent problem-solving skills with a focus on debugging and resolving migration challenges.
  • Strong communication and collaboration skills to work effectively with cross-functional teams and stakeholders.
  • Good-to-Have

  • Snowflake certifications such as SnowPro Core or Advanced Architect.
  • Knowledge of data governance and compliance frameworks (e.G., GDPR, HIPAA).
  • Familiarity with real-time data pipelines and streaming tools such as Apache Kafka or Spark.
  • Prior experience in large-scale data migrations and cloud-based data warehouse implementations.
  • Responsibility of / Expectations from the Role : -

  • Design and implement scalable ETL / ELT pipelines to migrate data from Excel sources to Snowflake.
  • Analyze and understand Excel data structures, transforming them into Snowflake-compatible formats.
  • Optimize Snowflake performance by implementing best practices such as clustering and partitioning.
  • Collaborate with business and technical teams to define migration requirements and strategies.
  • Automate data workflows using tools like Python, dbt, or Airflow for seamless migration processes.
  • Ensure data accuracy, quality, and integrity throughout the migration lifecycle.
  • Implement data security measures and ensure compliance with organizational and industry standards.
  • Stay updated with Snowflake’s latest features and industry trends to propose continuous improvements.
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