Data Engineer ( Snowflakes + AWS)

Experience - 5 + Years

Skills- Snowflakes + AWS

About the Role

We are seeking a highly skilled

Snowflake + AWS Engineer

with strong expertise in cloud-based data engineering, ETL pipeline development, and modern data warehouse architecture. The ideal candidate will have a proven track record of implementing scalable, high-performance data solutions using

Snowflake

on

AWS Cloud .

Key Responsibilities

Design, develop, and maintain

data pipelines

using Snowflake, AWS services, and Python / SQL-based ETL tools.

Architect and implement

data models ,

schemas , and

warehouse structures

optimized for analytics and reporting.

Manage and optimize

Snowflake environments , including performance tuning, cost optimization, and role-based access control.

Build and orchestrate

data workflows

using AWS services such as

Glue ,

Lambda ,

Step Functions ,

S3 , and

Athena .

Integrate data from multiple sources (APIs, RDBMS, flat files, streaming data, etc.) into Snowflake.

Implement and manage

data security, governance, and compliance

standards across platforms.

Collaborate with Data Scientists, Analysts, and DevOps teams to ensure data availability, accuracy, and reliability.

Monitor and troubleshoot production data pipelines and performance issues.

Implement

CI / CD automation

for data pipelines using tools like

Terraform, CloudFormation, or Jenkins .

Required Skills & Qualifications

Bachelor’s or Master’s degree in Computer Science, Engineering, or related field.

5+ years

of experience in

data engineering , with at least

2+ years of hands-on Snowflake experience .

Strong proficiency in

SQL

and

Python

for data transformation and automation.

Hands-on experience with

AWS Cloud services : S3, Glue, Lambda, Redshift, IAM, CloudWatch, and Step Functions.

Experience with

ETL / ELT tools

such as

dbt, Airflow, Talend, or Informatica Cloud .

Solid understanding of

data warehousing concepts ,

star / snowflake schemas , and

data modeling

techniques.

Knowledge of

data security, encryption, and key management

on AWS and Snowflake.

Strong analytical, problem-solving, and performance tuning skills.

Experience with

version control (Git)

and

CI / CD pipelines

for data projects.

Good to Have

Experience with

Databricks

or

Apache Spark .

Exposure to

Terraform ,

Kubernetes , or

Docker

for deployment automation.

Familiarity with

AWS cost optimization

and

FinOps best practices .

Knowledge of

modern data architectures

such as

Data Lakehouse

or

Data Mesh .

Soft Skills

Excellent communication and documentation skills.

Ability to work in agile, fast-paced environments.

Strong sense of ownership, accountability, and teamwork.