
Data Engineer
6 days ago
Job Title:
Data Engineer (AWS)
About the Role:
We are looking for an experienced Data Engineer with strong expertise in building and managing ETL pipelines and data workflows on AWS. The ideal candidate will have deep hands-on experience with AWS services such as Glue, S3, Redshift, Lambda, and Athena, as well as data tools like Airbyte and DBT. This role requires strong data modeling, Python, and SQL skills, and the ability to design scalable, fault-tolerant, and high-performing data systems.
Key Responsibilities:
Data Pipeline Development
- Design, develop, and maintain robust ETL pipelines for ingestion, transformation, and loading of structured and unstructured data.
- Implement exception handling, monitoring, and alerting mechanisms for data workflows.
AWS Data Architecture
- Build and optimize data workflows using AWS services such as Glue, S3, Lambda, Redshift, Athena, and Step Functions.
- Ensure data security, cost optimization, and scalability in AWS environments.
Data Modeling & Integration
- Design and maintain data models to support analytics, reporting, and downstream data use cases.
- Integrate multiple data sources using Airbyte and manage transformation layers with DBT.
Performance Optimization
- Tune SQL queries, optimize job performance, and handle large-scale data processing efficiently.
- Implement best practices for data quality, lineage, and metadata management.
Collaboration & Delivery
- Work closely with analytics, product, and engineering teams to deliver reliable data solutions aligned with business goals.
- Document workflows and ensure smooth CI/CD integration for data pipeline deployments.
Required Skills & Experience:
- 5+ years of experience as a Data Engineer or in a similar data-focused role.
- Strong proficiency in Python for ETL development and automation.
- Advanced SQL skills for complex data transformations and analysis.
- Hands-on experience with AWS data stack — Glue, S3, Redshift, Lambda, Athena, Step Functions.
- Proven experience in ETL pipeline development, data modeling, and workflow orchestration.
- Familiarity with Airbyte and DBT for data integration and transformation.
- Strong understanding of data quality, exception handling, and pipeline monitoring.
Preferred Skills:
- Experience with PySpark or other distributed processing frameworks.
- Familiarity with Terraform or other Infrastructure-as-Code tools.
- Exposure to DevOps practices and CI/CD pipelines for data projects.
- Experience with data warehousing and BI tools (e.g., Tableau, Power BI, QuickSight).
Qualifications:
- Bachelor's or Master's degree in Computer Science, Information Systems, or a related technical field.
- AWS certification (e.g., AWS Certified Data Analytics – Specialty or AWS Solutions Architect) is a plus.
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