osition: AWS & Snowflake Data Engineer
Location: Onsite / Hybrid
Employment Type: Full-time / Contract
Overview
We are seeking an experienced AWS & Snowflake Data Engineer to design, build, and maintain cloud-based data pipelines, warehouses, and analytics platforms. The ideal candidate will have a strong background in AWS data services, Snowflake architecture, and ETL/ELT development using modern data engineering practices.
You will be responsible for building scalable, cost-efficient data solutions that support advanced analytics, business intelligence, and machine learning initiatives.
Key Responsibilities
Data Architecture & Development
- Design, develop, and optimize data pipelines to ingest data from multiple sources into Snowflake using AWS Glue, Lambda, Step Functions, or Airflow.
- Create and manage Snowflake databases, warehouses, schemas, roles, and access controls.
- Develop ETL/ELT processes to transform, cleanse, and load structured and semi-structured data (JSON, Parquet, etc.).
- Implement data modeling best practices (Star/Snowflake schema) for analytics and reporting.
- Use Python, SQL, or PySpark to automate data integration and validation.
Cloud Infrastructure (AWS)
- Leverage AWS S3, Glue, Lambda, Redshift, Kinesis, Step Functions, and CloudFormation/Terraform for data architecture and automation.
- Manage IAM roles, networking, and resource configuration for secure and efficient access to Snowflake and AWS services.
- Implement monitoring, logging, and cost optimization for data workflows using CloudWatch and other observability tools.
Data Quality, Security & Governance
- Ensure data accuracy, completeness, and consistency across environments.
- Implement data lineage and cataloging using tools such as AWS Glue Data Catalog or Collibra.
- Enforce security and compliance through role-based access control, encryption, and auditing.
Collaboration & Delivery
- Work closely with Data Analysts, Scientists, and BI Developers to enable self-service data access.
- Partner with business stakeholders to understand data needs and translate them into scalable technical solutions.
- Participate in code reviews, architecture discussions, and CI/CD deployments for data workflows.
Required Skills
- 5+ years of experience in Data Engineering or related field.
- Strong experience with AWS Data Services (S3, Glue, Lambda, Redshift, Step Functions).
- Hands-on expertise in Snowflake (data warehousing, schema design, query optimization).
- Proficiency in SQL and Python/PySpark for data transformations.
- Experience with data pipeline orchestration (Airflow, Step Functions, or similar).
- Solid understanding of data modeling, performance tuning, and cost management.
- Familiarity with version control (Git) and CI/CD pipelines (CodePipeline, Jenkins, or GitHub Actions).
Preferred Skills
- Experience with Databricks or EMR for large-scale data processing.
- Exposure to API-based data ingestion (REST, GraphQL).
- Knowledge of data cataloging and lineage tools (Purview, Collibra, Alation).
- Familiarity with Terraform or CloudFormation for IaC.
- Experience in Agile/Scrum environments.
