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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

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