Xperteez Technology

🌎 Data Engineer, Remote - Full Time

Xperteez Technology United States · $140K–$180K/yr

Business Consulting and Services · 51-200 employees

9 h ago
Remote data-engineer Mid (2-5 yrs) Full-time United States
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About the role

Design, build, and maintain scalable data pipelines and storage solutions to support AI-driven products and research. Collaborate with cross-functional teams to ensure data quality, operational reliability, and efficient processing workflows.

What they look for

Python SQL Spark AWS Data engineering Distributed systems Data pipelines NoSQL Data architecture Cloud computing Data processing Automation Orchestration Data quality AI/ML workflows

Requirements

Requires strong proficiency in Python, SQL, and Apache Spark, along with hands-on experience in AWS cloud-native data architectures. Candidates should have experience managing large-scale datasets and working with both SQL and NoSQL database systems.

Benefits

Equity compensation Performance-based bonuses Health insurance reimbursement Paid time off 401(k) plan

Full description

Job Title: Data Engineer

Job Type: Full-time

Location: Remote

We are looking for a Data Engineer to build and scale the data infrastructure that powers AI-driven products and research initiatives. In this role, you will develop distributed data pipelines, manage large-scale datasets across cloud environments, and design reliable data systems that support data processing, experimentation, and model development at scale.

Required Skills

  • Python
  • SQL
  • AI/ML
  • Spark
  • AWS

Key Responsibilities

  • Design, build, and maintain scalable data pipelines to ingest, process, and transform large-scale datasets from multiple sources.
  • Develop and optimize distributed data processing workflows using Spark and cloud-native technologies.
  • Build and maintain data storage solutions across SQL and NoSQL systems, ensuring scalability, performance, and reliability.
  • Design and implement data architectures on AWS to support high-volume data ingestion, processing, and distribution.
  • Write efficient Python and SQL code to extract, transform, validate, and analyze large datasets.
  • Ensure data quality, integrity, monitoring, and operational reliability across data pipelines and storage layers.
  • Collaborate with AI researchers, data scientists, and engineering teams to support data-intensive applications and experimentation.
  • Implement automation, orchestration, and monitoring workflows to support scalable and efficient data operations.

Required Skills and Qualifications

  • Strong proficiency in Python, SQL, and distributed data processing frameworks such as Apache Spark.
  • Hands-on experience with AWS data services and cloud-native data architectures.
  • Experience working with both SQL and NoSQL databases.
  • Experience managing and processing large-scale datasets in distributed environments.
  • Strong understanding of data partitioning, performance optimization, and scalable data architectures

Nice to Have

  • Exposure to AI/ML workflows or research environments.
  • Experience with data visualization tools such as Matplotlib, Seaborn, or Plotly.
  • Familiarity with LLM-related data workflows (datasets for training, evaluation, or prompt experimentation).

Compensation & Benefits Notice

All employees are eligible for equity compensation, and employees may also receive performance-based bonuses, dependent on role and subject to company policies. Comprehensive benefits package, including up to 100% reimbursement for health-insurance premiums, paid time off, a 401(K) plan with a company match, and additional benefits designed to support a high-performing, remote-first workforce.

Disclaimer

The information contained in this job posting, including but not limited to role responsibilities, qualifications, compensation, and benefits, is provided for informational purposes only and does not constitute a binding offer of employment. micro1 reserves the right to amend, modify, or withdraw any portion of this posting at its sole discretion and without prior notice. All employment decisions are made in accordance with applicable laws and regulations.

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