AWS Data Engineer

AWS Data Engineer

📍 Location: New York, New York, United States

🏢 Industry: IT Services and IT Consulting

💼 Work Setting: Onsite

Are you passionate about building scalable data platforms, designing cloud-native data solutions, and enabling data-driven decision-making through modern engineering practices? We are seeking an experienced AWS Data Engineer to design, develop, and optimize robust data architectures and pipelines that support analytics, reporting, and business intelligence initiatives.

In this role, you will be responsible for developing scalable data solutions, managing large datasets, and ensuring data quality, reliability, and performance across cloud-based environments. You will work closely with business stakeholders, analysts, and engineering teams to transform raw data into valuable insights that drive strategic decision-making.

Key Responsibilities

Data Pipeline Development

• Design, develop, and maintain scalable ETL/ELT pipelines to support data integration, transformation, and analytics requirements.
• Build reliable and efficient data workflows capable of processing large volumes of structured and unstructured data.
• Optimize data ingestion, transformation, and delivery processes to improve performance and scalability.

Cloud Data Engineering

• Architect and implement cloud-based data solutions that support enterprise reporting, analytics, and operational workloads.
• Design and manage scalable data lakes, data warehouses, and data processing platforms.
• Ensure high availability, performance, and reliability of cloud data infrastructure.

Data Architecture & Integration

• Develop data models and architectures that support current and future business requirements.
• Integrate data from multiple internal and external sources into centralized platforms.
• Ensure data consistency, governance, and accessibility across the organization.

Data Quality & Governance

• Implement processes and controls to maintain data accuracy, integrity, and reliability.
• Support data governance initiatives, including metadata management, data lineage, and compliance requirements.
• Monitor and resolve data quality and performance issues proactively.

Performance Optimization

• Analyze and optimize data processing workflows, queries, and storage solutions.
• Improve efficiency and scalability of data platforms to support growing business demands.
• Implement best practices for monitoring, troubleshooting, and capacity planning.

Collaboration & Stakeholder Engagement

• Work closely with analytics, business intelligence, product, and application development teams to understand data requirements.
• Translate business needs into scalable technical solutions.
• Partner with cross-functional teams to deliver high-quality data products and insights.

Modern Data Technologies

• Support streaming, batch processing, and real-time data integration solutions.
• Evaluate and implement emerging technologies that improve data engineering capabilities.
• Contribute to continuous improvement initiatives and engineering best practices.

Required Qualifications

• Bachelor’s degree in Computer Science, Engineering, Information Technology, or a related field.
• 3 to 8+ years of experience in Data Engineering, Data Platform Development, or related roles.
• Strong hands-on experience with AWS cloud services and cloud-based data architectures.
• Advanced SQL skills for querying, transformation, and optimization of large datasets.
• Proficiency in Python and experience with data engineering frameworks and automation.
• Experience designing and supporting ETL/ELT pipelines.
• Strong understanding of data warehousing concepts and data lake architectures.
• Experience working with large-scale datasets in distributed computing environments.
• Strong analytical, troubleshooting, and problem-solving abilities.
• Excellent communication and collaboration skills.

Preferred Technical Skills

• AWS Cloud Services
• Data Engineering
• ETL/ELT Development
• Data Lakes
• Data Warehousing
• SQL
• Python
• Spark
• Kafka
• Hadoop
• Distributed Data Processing
• Data Modeling
• Data Integration
• Cloud Architecture
• Performance Optimization