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Open nowPosted 274 days ago

Senior Snowflake Developer

QualMinds Technologies16 open roles

Where
Hyderabad
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Your applicationOpen nowSenior Snowflake DeveloperQualMinds Technologies · Hyderabad

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The clock on this job

Early applications get read.

11.5% of postings close within 7 days. Measured by our own scanner across the market.

Share of postings closed within
  1. 2.1%1 day
  2. 4.4%3 days
  3. 11.5%7 days
  4. 18.1%14 days
  5. 35.6%30 days
  6. 44.6%60 days
This job: posted 274 days ago

The posting

Senior Snowflake Developer – JD

About QualMinds:

We at QualMinds design & develop world-class digital products and custom software for Startups, Scale-ups & Enterprises with our world-class engineering team.

We assemble a great team of frontend, backend, full-stack, QA automation, UI/UX, DevOps, data science, machine learning, and agile experts to help our clients propel their pursuit of digital excellence.

Our engineering community at QualMinds is always passionate about building customer-centric software with the highest quality, performance, security, scalability, and lowest failure rates.

We are looking for an experienced Snowflake Developer / Senior Data Engineer with strong expertise in building scalable data pipelines, optimizing Snowflake environments, and delivering high-quality data solutions. The ideal candidate will have 5–10 years of hands-on experience in data engineering with a deep understanding of Snowflake, SQL, and cloud-based ETL tools.

Key Responsibilities

1. Snowflake Development & Architecture

  • Design and develop scalable Snowflake data models including fact, dimension, and staging layers.
  • Define and implement clustering keys, partition strategies, and effective micro-partition usage for large tables.
  • Optimize Snowflake storage and compute architecture based on business workloads.

2. Data Ingestion & Pipeline Development

  • Build and maintain ETL/ELT pipelines using: Snowflake SQL, Snowpipe, Azure Data Factory (ADF), Matillion
  • Implement incremental / delta load mechanisms and ensure data freshness.
  • Perform data validation, deduplication, and consistency checks across sources and targets.

3. SQL & Stored Procedure Development

  • Write complex SQL queries, views, and stored procedures using: Snowflake Scripting, JavaScript (for Snowflake stored procedures)
  • Conduct SQL performance tuning and query optimization.

4. Performance Tuning & Optimization

  • Analyze and troubleshoot slow-running queries using Query Profile and Snowflake monitoring tools.
  • Optimize performance through warehouse sizing, caching strategies, micro-partition pruning, and query structure improvements.
  • Ensure efficient resource consumption and cost optimization.

5. Security, Governance & Access Control

  • Implement and maintain RBAC (Role-Based Access Control).
  • Manage roles, users, privileges, and secure data sharing.
  • Ensure compliance with organizational security standards and best practices.

6. Monitoring, Troubleshooting & Operations

  • Implement robust error handling including logging, retry mechanisms, and alerting.
  • Monitor pipeline performance and proactively identify issues.
  • Collaborate with cross-functional teams for requirement gathering, solution design, and production support.

Required Skills & Qualifications

  • 5–10 years of experience in Data Engineering or related roles.
  • 3+ years hands-on experience working with Snowflake.
  • Strong expertise in SQL, stored procedures, and performance tuning.
  • Hands-on experience with ETL/ELT tools such as Azure Data Factory, Matillion, or Snowpipe.
  • Solid understanding of data warehousing concepts, dimensional modeling, and data architecture.
  • Experience with RBAC, security best practices, and data governance.
  • Familiarity with cloud platforms (Azure/AWS/GCP preferred).
  • Strong debugging, problem-solving, and analytical skills.
  • Bachelor’s or Master’s degree in Computer Science, Information Technology, Engineering, or related field.

Preferred Skills

  • Experience with Python or PySpark for data pipeline development.
  • Exposure to CI/CD, DevOps practices, and Git-based development workflows.
  • Knowledge of monitoring tools and performance analytics.
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