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, CloudWatch, or EventBridge.
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
SnowPro Core
SnowPro Advanced: Data Engineer
SnowPro 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.

Data Engineer Analytics & AWS