AI-First Data Engineer

Inspire11; United States; On-site; USD 90,000 - 147,000; Full time

Benefits offered by this job

Medical insurance

Dental insurance

Vision insurance

401(k) plan

Paid time off

Parental leave

Job summary

Inspire11 is seeking a Data Engineer to design and build scalable data pipelines powering analytics and AI initiatives. You will work hands-on with Python, PySpark, and SQL across cloud platforms to transform raw data into trusted assets for client value.

You will develop AI-first data solutions on modern platforms and collaborate with business and technical teams to deliver reliable data products with strong governance and quality controls.

Qualifications

• Bachelor’s degree in Computer Science, Engineering, or related field.
• 3+ years of experience in data engineering, analytics engineering, or software development.
• Proficiency in SQL and Python with hands-on data pipelines.
• Experience with cloud hyperscalers (AWS/Azure/GCP) and modern data stacks.

Responsibilities

• Design and build scalable data pipelines using Python, PySpark, SQL to ingest, transform, and prepare data for analytics and AI use cases.
• Develop AI-first, cloud-native data solutions on Fabric, Databricks, Snowflake, Synapse, or Redshift.
• Define ingestion patterns for structured and unstructured data and ensure data quality.
• Create BI-ready datasets and support reporting, dashboards, and AI use cases.
• Collaborate with teams to translate requirements into clear technical designs.

Skills

SQL

Python

PySpark

Data pipelines

CI/CD

Git

Communication

Education

Bachelor’s degree in Computer Science or Engineering

Tools

AWS

Azure

GCP

Databricks

Snowflake

Fabric

Synapse

Redshift

Job description

Inspire11 is seeking a Data Engineer to design and build scalable data pipelines powering analytics and AI initiatives. You will work hands-on with Python, PySpark, and SQL across cloud platforms to transform raw data into trusted assets for client value.

You will develop AI-first data solutions on modern platforms and collaborate with business and technical teams to deliver reliable data products with strong governance and quality controls.