Data Engineer – Analytics & AWS

Role Overview :
We are looking for a  Data Engineer – Analytics & AWS  with  2–4 years of experience  who enjoys working across both  data engineering and data analytics .
In this role, you will build and support scalable data pipelines while also working with data for  analysis, data quality, transformation, and analytics use cases . You will work with modern AWS and Snowflake technologies and collaborate with cross-functional teams to deliver reliable, business-ready data solutions.
The ideal candidate has strong hands-on experience with  AWS Glue, S3, SQL, Python, and Snowflake , along with a good understanding of ETL/ELT and data analytics.

What You'll Work On:
Data Engineering
Design, develop, and maintain ETL/ELT pipelines for data ingestion, transformation, and loading.
Build and support data pipelines using  AWS Glue and Amazon S3 .
Develop Python-based data processing and automation solutions.
Build and optimize data warehouse solutions using  Snowflake .
Develop and support workflow orchestration using  Airflow  and related services.
Work with event-driven and streaming workflows using  Kafka .
Troubleshoot production issues and improve pipeline performance, scalability, and reliability.
Data Analytics
Analyze data to identify trends, issues, and insights.
Use  SQL and Snowflake  for data analysis, validation, and investigation.
Support data quality and reconciliation activities across multiple data sources.
Work with business and technical teams to understand analytics requirements.
Translate data findings into practical technical solutions.
Support analytics and reporting use cases across multiple projects.

Key Responsibilities:

Work on projects across  Data Ingestion, Data Transformation, Data Quality, and Data Analytics .
Develop efficient SQL queries for transformation, validation, and analytics.
Implement and maintain Snowflake capabilities including  RBAC, ABAC, Snowpipes, and Dynamic Tables .
Develop AWS Glue ETL workflows and Python Shell jobs.
Work with AWS services including  Glue, Lambda, SNS, and S3 .
Ensure data accuracy, consistency, security, and operational reliability.
Investigate data issues and perform root-cause analysis.
Collaborate with engineers, analysts, and other stakeholders to understand requirements and deliver solutions.
Document data processes, architecture, workflows, and operational procedures.
Manage multiple projects and priorities based on business and team requirements.

Core Technical

Skills:

AWS
AWS Glue
AWS S3
AWS Lambda
AWS SNS
Data & Analytics
SQL
Snowflake
ETL/ELT
Data Warehousing
Data Quality
Data Analysis
Programming
Python
Data & Workflow Technologies
Airflow
Kafka

What You'll Bring:
2–4 years of experience  in Data Engineering, Analytics Engineering, Software Development, or a related field.
Strong hands-on experience with  SQL and Python .
Experience building or supporting  ETL/ELT pipelines .
Hands-on experience with  AWS Glue and S3 .

Working experience with  Snowflake .
Experience working with data for both  engineering and analytical purposes .
Strong analytical, debugging, and problem-solving skills.
Ability to work on multiple projects and manage changing priorities.
Strong collaboration and communication skills.
An ownership mindset and attention to detail.
Ability to learn new technologies and work effectively in a fast-paced Agile environment.

Good to Have:

Experience with  Pentaho  for ETL/data integration.
Exposure to AWS  EMR, Redshift, Athena, Step Functions, IAM, Cloud Watch, or Event Bridge .
Working knowledge of  Kafka  and streaming architectures.
Familiarity with data lakes and distributed systems.
Understanding of data governance, security, and access controls.
Experience working with analytics, reporting, or business intelligence use cases.
Relevant certifications such as:
AWS Certified Cloud Practitioner
AWS Certified Data Engineer – Associate
AWS Certified Developer – Associate
Snow Pro Core
Snow Pro Advanced:
Data Engineer
Snow Pro Specialty:
Snowpark

Education:

Bachelor's degree in  Computer Science, Information Technology, Engineering, or a related field .

Why This Role?

Join a collaborative  Data Engineering team  working on diverse projects across  data ingestion, data transformation, data quality, and analytics .

This role offers hands-on exposure to both  Data Engineering and Analytics , with opportunities to work with modern  AWS, Snowflake, Python, and SQL technologies .