Data Engineer

Data Engineer (3–4 Years Experience)

Location: United States (Remote / On-site – based on client needs)

Employment Type: Full-time (Contract or Contract-to-Hire)

Experience Level: Mid-level (3–4 years)

Company: Aaratech Inc

🛑 Eligibility: Open to U.S. Citizens and Green Card holders only. We do not offer visa sponsorship.

🔍 About Aaratech Inc

Aaratech Inc is a specialized IT consulting and staffing company that places elite engineering talent into high-impact roles at leading U.S. organizations. We focus on modern technologies across cloud, data, and software disciplines. Our client engagements offer long-term stability, competitive compensation, and the opportunity to work on cutting-edge data projects.

🎯 Position Overview

We are seeking a Data Engineer with 3–4 years of experience to join a client-facing role focused on building and maintaining scalable data pipelines, robust data models, and modern data warehousing solutions. You'll work with a variety of tools and frameworks, including Apache Spark, Snowflake, and Python, to deliver clean, reliable, and timely data for advanced analytics and reporting.

🛠️ Key Responsibilities

• Design and develop scalable Data Pipelines to support batch and real-time processing
• Implement efficient Extract, Transform, Load (ETL) processes using tools like Apache Spark and dbt
• Develop and optimize queries using SQL for data analysis and warehousing
• Build and maintain Data Warehousing solutions using platforms like Snowflake or BigQuery
• Collaborate with business and technical teams to gather requirements and create accurate Data Models
• Write reusable and maintainable code in Python (Programming Language) for data ingestion, processing, and automation
• Ensure end-to-end Data Processing integrity, scalability, and performance
• Follow best practices for data governance, security, and compliance

✅ Required Skills & Experience

• 3–4 years of experience in Data Engineering or a similar role
• Strong proficiency in SQL and Python (Programming Language)
• Experience with Extract, Transform, Load (ETL) frameworks and building data pipelines
• Solid understanding of Data Warehousing concepts and architecture
• Hands-on experience with Snowflake, Apache Spark, or similar big data technologies
• Proven experience in Data Modeling and data schema design
• Exposure to Data Processing frameworks and performance optimization techniques
• Familiarity with cloud platforms like AWS, GCP, or Azure

⭐ Nice to Have

• Experience with streaming data pipelines (e.g., Kafka, Kinesis)
• Exposure to CI/CD practices in data development
• Prior work in consulting or multi-client environments
• Understanding of data quality frameworks and monitoring strategies