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
