Data Engineer

Appsierra Group; United States; On-site; USD 140,000 - 180,000; Full time

Benefits offered by this job

Equity

Performance bonuses

Health insurance reimbursement

Paid time off

401(k) matching

Remote-first workforce

Job summary

Appsierra Group is seeking a Data Engineer to design and scale data infrastructure powering AI‑driven products. You will build distributed pipelines, manage large datasets across cloud environments, and develop reliable systems to support experimentation and model development at scale.

The role emphasizes Python and SQL coding, data quality, and collaboration with AI researchers and engineers to deliver data‑intensive applications in a remote‑first, high‑performance team.

Qualifications

• Strong proficiency in Python, SQL, and distributed frameworks (Apache Spark).
• Hands‑on experience with AWS data services and cloud‑native architectures.
• Experience with SQL and NoSQL databases.
• Proven ability to manage and process large‑scale datasets in distributed environments.

Responsibilities

• Design, build, and maintain scalable data pipelines for ingestion, processing, and transformation
• Develop distributed workflows using Spark and cloud‑native technologies
• Build and maintain SQL/NoSQL storage solutions for performance and reliability
• Architect AWS‑based systems for high‑volume data ingestion and distribution
• Write efficient Python and SQL code for ETL and analysis
• Ensure data quality, integrity, monitoring, and operational reliability
• Collaborate with AI researchers, data scientists, and engineers on data‑intensive applications
• Implement automation, orchestration, and monitoring workflows for scalable operations

Skills

Python

SQL

AI/ML

Spark

AWS

Job description

Data Engineer

Remote | Full‑time | $140,000–$180,000/year | 1 Opening

About the Role

Build and scale the data infrastructure powering AI‑driven products and research. Develop distributed data pipelines, manage large‑scale datasets across cloud environments, and design reliable systems that support experimentation and model development at scale.

Key Responsibilities

• Design, build, and maintain scalable data pipelines for ingestion, processing, and transformation
• Develop distributed workflows using Spark and cloud‑native technologies
• Build and maintain SQL/NoSQL storage solutions for performance and reliability
• Architect AWS‑based systems for high‑volume data ingestion and distribution
• Write efficient Python and SQL code for ETL and analysis
• Ensure data quality, integrity, monitoring, and operational reliability
• Collaborate with AI researchers, data scientists, and engineers on data‑intensive applications
• Implement automation, orchestration, and monitoring workflows for scalable operations

Required Skills

• Python
• SQL
• AI/ML
• Spark
• AWS

Qualifications

• Strong proficiency in Python, SQL, and distributed frameworks (Apache Spark)
• Hands‑on experience with AWS data services and cloud‑native architectures
• Experience with SQL and NoSQL databases
• Proven ability to manage and process large‑scale datasets in distributed environments
• Understanding of data partitioning, performance optimization, and scalable architectures

Nice to Have

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

Compensation & Benefits

• Pay range: $140,000–$180,000/year
• Equity compensation eligibility
• Performance‑based bonuses
• Comprehensive benefits package including:
  • Up to 100% reimbursement for health‑insurance premiums
  • Paid time off
  • 401(K) plan with company match
  • Additional benefits supporting a high‑performing, remote‑first workforce

Equal Opportunity

All qualified applicants will receive consideration without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, genetic information, veteran status, or any other characteristic protected by law.