Data Engineer

IntePros; Dallas (TX); On-site; USD 90,000 - 140,000; Full time

Job summary

IntePros is seeking a passionate Data Engineer to design and build scalable data solutions that empower business teams with timely insights. You will work in a large, complex data environment, developing data infrastructure, pipelines, and analytical solutions that provide reliable access to business data.

Ideal candidates combine strong SQL and Python skills with hands-on ETL experience and the ability to translate business requirements into scalable data solutions.

Qualifications

• Bachelor’s degree in a related field.
• 3+ years of data engineering experience.
• Strong SQL proficiency and data analysis skills.
• Strong Python knowledge for data engineering and automation.
• 3+ years in data modeling, warehousing, and ETL development.
• Experience with large-scale BI/analytics data structures.

Responsibilities

• Design, build, and maintain scalable data pipelines and ETL processes.
• Develop and support analytical technologies for reliable data access.
• Use SQL and Python to transform, analyze, and automate data workflows.
• Design data solutions for BI, analytics, and reporting needs.
• Develop data models and structures to enable efficient reporting.
• Build and support dashboards using BI tools.
• Partner with stakeholders to translate requirements into solutions.
• Apply best practices to improve scalability, reliability, and data quality.
• Support large-scale data structures ensuring accuracy and consistency.

Skills

SQL & Data Analysis

Python

ETL & Data Pipelines

Data Modeling & Warehousing

AWS Data Technologies

Education

Bachelor’s degree

Tools

Redshift

S3

AWS Glue

EMR

Kinesis

Firehose

Lambda

IAM roles and permissions

Job description

Overview

We are seeking a passionate, innovative, and results-oriented Data Engineer to design and build scalable data solutions that empower business teams with reliable, actionable insights. This role will work within a large and complex data environment, developing data infrastructure, pipelines, and analytical solutions that provide timely and flexible access to business data.

The ideal candidate combines strong SQL and Python expertise with hands-on ETL experience and the ability to translate business requirements into scalable data solutions.

Key Responsibilities

• Design, build, and maintain scalable data pipelines and ETL processes.
• Develop and support analytical technologies that provide reliable and structured access to business data.
• Use SQL and Python to transform, analyze, and automate data workflows.
• Design and implement data solutions that support business intelligence, analytics, and reporting needs.
• Develop data models and structures that enable efficient reporting and analytics.
• Build and support reports and dashboards using business intelligence and reporting tools.
• Partner with business stakeholders to understand requirements and translate them into effective technical solutions.
• Apply data engineering best practices to improve scalability, reliability, data quality, and performance.
• Support data structures and pipelines operating at large scale while ensuring accuracy and consistency.

Required Qualifications

• Bachelor’s degree.
• 3+ years of data engineering experience.
• Strong SQL proficiency and data analysis skills.
• Strong Python knowledge and hands‑on experience using Python for data engineering and automation.
• 3+ years of experience with data modeling, data warehousing, and ETL pipeline development.
• Experience developing and operating large-scale data structures for business intelligence and analytics.
• Ability to understand business requirements and translate them into scalable data solutions.

Preferred Qualifications

• Experience with AWS technologies such as:
• Redshift
• S3
• AWS Glue
• EMR
• Kinesis
• Firehose
• Lambda
• IAM roles and permissions
• Experience with non‑relational databases and data stores, including object storage, document or key‑value stores, graph databases, or column‑family databases.
• Strong experience with data modeling and data warehousing.
• Experience building and operating large-scale data structures for business intelligence and analytics.
• Experience with data quality automation, orchestration, and pipeline tooling beyond SQL.

Top Skills

• SQL & Data Analysis – Advanced SQL fluency and ability to analyze complex datasets.
• Python – Strong Python development skills for automation, orchestration, and data engineering.
• ETL & Data Pipelines – Strong hands‑on experience designing, developing, and supporting ETL pipelines.
• Data Modeling & Warehousing – Experience creating scalable data structures that support analytics and reporting.
• AWS Data Technologies – Experience with cloud‑based data engineering services is highly valued.

Leadership & Success Profile

The Successful Candidate Will Demonstrate

• Deliver Results: Consistently deliver reliable, scalable data solutions that meet business needs and deadlines.
• Ownership: Take end‑to‑end responsibility for data pipelines, solutions, and outcomes while proactively identifying and resolving issues.
• Strong analytical and problem‑solving abilities.
• Ability to work independently while collaborating effectively with technical and business stakeholders.
• Attention to data quality, reliability, and operational excellence.
• Ability to operate effectively in a complex, large-scale data environment.