Snowflake developer

We’re Hiring | Snowflake Full Stack Developer 5 + Years of exp is must needed

Location: Hyderabad (hybrid)

Seeking a skilled Data Engineer to design, build, and optimize modern data pipelines and analytics platforms. The ideal candidate will have strong hands-on experience with Snowflake, dbt, Airflow, and Python/Spark, along with solid SQL and data modeling skills. You’ll collaborate with cross-functional teams—data analysts, data scientists, and business stakeholders—to ensure data reliability, scalability, and Performance.

🔧 Tech Stack

Snowflake | Python | SQL | DBT | Cloud (AWS/Azure/GCP) | Git | Airflow

Key Responsibilities

• Design, develop, and maintain data pipelines for ingestion, transformation, and delivery using Airflow, DBT, and Snowflake.
• Implement and optimize ETL/ELT workflows for structured and semi-structured data.
• Develop and maintain data models, schemas, and views in Snowflake to support analytics and reporting.
• Build and manage data processing frameworks using Spark (PySpark or Spark SQL).
• Integrate data from various sources (databases, APIs, files, cloud storage, streaming data).
• Monitor data pipelines for performance, reliability, and cost optimization.
• Implement data quality checks, observability, and error handling mechanisms.
• Collaborate with data analysts/scientists to understand data needs and deliver scalable solutions.
• Apply CI/CD best practices for data pipeline deployment and version control (Git).
• Ensure compliance with data governance, security, and privacy policies.

Required Skills & Experience

• 5–7 years of experience in data engineering or a related field.
• Strong expertise with Snowflake (warehousing concepts, performance tuning, cost optimization, security).
• Proven experience with dbt (data modeling, testing, documentation, modular SQL).
• Hands-on experience with Apache Airflow (DAG design, scheduling, orchestration).
• Proficiency in SQL and Python for data manipulation and automation.
• Experience with Apache Spark (PySpark preferred).
• Strong understanding of ETL/ELT design patterns, data modeling (Kimball, Data Vault), and dimensional modeling.
• Experience with Git, CI/CD, and Cloud Platforms (AWS, Azure, or GCP).
• Knowledge of data quality, observability, and monitoring tools (e.g., Great Expectations, Monte Carlo, or similar).