Data Engineer

Infojini Inc; India; On-site; INR 1,200,000 - 1,800,000; Full time

Job summary

Infojini Inc. is seeking a highly skilled Snowflake Data Engineer to design, develop, and optimize scalable data pipelines using Snowflake, Python and PySpark for large-scale data integration and analytics initiatives. Immediate joiners only.

You will migrate legacy workloads to the cloud, optimize Snowflake objects, and implement robust data models, RBAC and governance to support GDPR/CCPA compliance. Expertise in Snowflake features (Snowpipe, Time Travel, Cloning), dbt, Airflow, and cloud

Qualifications

• 3+ years of experience in data engineering, with 1-2 years focused on Snowflake ecosystem.
• Bachelor's or Master's degree in Computer Science, Data Engineering, or a related field.
• Deep expertise in Snowflake features: Snowpipe, Tasks, Streams, Zero-Copy Cloning, Time Travel.
• Proficiency in Python and SQL; able to write clean, PEP8-compliant code.
• Experience with PySpark for large-scale data processing.
• Familiarity with RBAC, data masking, and GDPR/CCPA compliance.

Responsibilities

• Pipeline Development: Design and implement end-to-end ELT/ETL pipelines to ingest data from diverse sources into Snowflake.
• Data Transformation: Utilize PySpark for heavy-duty distributed processing and Python (Snowpark) for procedural logic and data manipulation within the Snowflake environment.
• Snowflake Optimization: Manage and optimize Snowflake objects including Virtual Warehouses, Stages, Pipes, Streams, and Tasks.
• Advanced Scripting: Develop complex SQL queries, Stored Procedures (Python/SQL), and User Defined Functions.
• Performance Tuning: Use Query Profiling to identify bottlenecks and implement strategies like Clustering Keys and Search Optimization Service.
• Data Modeling: Design scalable data models (Star/Snowflake schema) and implement Data Vault or Medallion architectures.
• Security & Governance: Implement RBAC, data masking, and row-level security to ensure compliance with GDPR/CCPA.

Skills

Python

PySpark

SQL

Data modeling

Education

Bachelor's degree in Computer Science, Data Engineering, or related field

Master's degree in Computer Science, Data Engineering, or related field

SnowPro Core

Databricks/Spark Certified Developer

Tools

Snowflake

Snowpark

dbt

Airflow

Dagster

Git

Job description

We're hiring for Snowflake Data Engineer with Infojini

Job Summary

We are seeking a highly skilled Snowflake Data Engineer to design, develop, and optimize scalable data pipelines. The ideal candidate will leverage Snowflake's cloud-native features alongside Python and PySpark to handle complex data transformations and large-scale data integration. You will be instrumental in migrating legacy data workloads to the cloud and ensuring high-performance data delivery for analytics and AI/ML initiatives.

Immediate joiners only

Key Responsibilities

• Pipeline Development: Design and implement end-to-end ELT/ETL pipelines to ingest data from diverse sources (APIs, IoT streams, S3/Azure Blobs, On-premise databases) into Snowflake.
• Data Transformation: Utilize PySpark for heavy-duty distributed processing and Python (Snowpark) for procedural logic and data manipulation within the Snowflake environment.
• Snowflake Optimization: Manage and optimize Snowflake objects including Virtual Warehouses, Stages, Pipes (Snowpipe), Streams, and Tasks for cost and performance.
• Advanced Scripting: Develop complex SQL queries, Stored Procedures (Python/SQL), and User Defined Functions (UDFs) to support business logic.
• Performance Tuning: Use Query Profiling to identify bottlenecks and implement strategies like Clustering Keys and Search Optimization Service.
• Data Modeling: Design scalable data models (Star/Snowflake schema) and implement Data Vault or Medallion (Bronze/Silver/Gold) architectures.
• Security & Governance: Implement Role-Based Access Control (RBAC), data masking, and row-level security to ensure compliance with GDPR/CCPA.

Technical Requirements

• Cloud Warehouse: Deep expertise in Snowflake (Snowpipe, Tasks, Streams, Zero-Copy Cloning, Time Travel).
• Programming: Advanced Python and SQL. Ability to write clean, PEP8-compliant code.
• Big Data: Proficiency in PySpark (Spark Core, Spark SQL, DataFrames) for large-scale data processing.
• Frameworks: Experience with Snowpark and dbt (data build tool) for modular SQL development.
• Orchestration: Familiarity with tools like Apache Airflow, Prefect, or Dagster.
• Infrastructure: Hands-on experience with at least one cloud provider (AWS, Azure, or GCP).
• DevOps: Version control with Git, CI/CD pipelines, and automated testing (Pytest).

Education

• Bachelor's or Master's degree in Computer Science, Data Engineering, or a related field.

Professional Experience

• 3+ years of experience in data engineering, with at least 1-2 years focused specifically on the Snowflake ecosystem.

Certifications (Preferred)

• SnowPro Core or SnowPro Advanced Data Engineer; Databricks/Spark Certified Developer.