Data Engineer

MACHINE LEARNING TECHNOLOGIES LLC; Dallas (TX); On-site; USD 90,000 - 140,000; Full time

Job summary

Machine Learning Technologies LLC in Dallas, TX is seeking a Data Engineer to develop and maintain scalable data pipelines, perform ETL/ELT, and collaborate with data teams. The role emphasizes Python and SQL proficiency, relational database design, and cloud data platform support.

This contract position offers engagement through 12 months with potential extensions and multi-setup compensation. The candidate should have 1–3 years of data engineering experience, strong SQL/Python skills, and

Qualifications

• 1-3 years of professional Data Engineering or related experience.
• Strong proficiency in Python and SQL.
• Experience with ETL/ELT processes and data pipelines.
• Experience working with relational databases.
• Familiarity with Git and software development practices.

Responsibilities

• Develop and maintain scalable data pipelines and ETL workflows.
• Extract, transform, and load data from multiple sources.
• Write optimized SQL queries for data extraction and transformation.
• Develop data processing solutions using Python.
• Monitor data pipelines and troubleshoot data quality or processing issues.
• Work with data analysts, data scientists, software engineers, and business teams.
• Design and maintain data models and database structures.
• Implement data validation and quality checks.
• Optimize data pipelines for performance and reliability.
• Document data pipelines, processes, and technical solutions.
• Support cloud-based data platforms and data integration projects.
• Participate in Agile development and code reviews.

Skills

Python

SQL

ETL/ELT

Relational databases

Education

Bachelor's degree in Computer Science or related field

Tools

Git

Job description

Job Description

Job Overview

• Job ID: J53359
• Job Title: Data Engineer
• Location: Dallas, TX
• Duration: 12 Months + Extension
• Domain Exposure: Insurance
• Work Authorization: US Citizen,Green Card,OPT-EAD,CPT,H-1B,H4-EAD,L2-EAD,GC-EAD
• Client: To Be Discussed Later
• Employment Type: W-2, 1099, C2C

Responsibilities

• Develop and maintain scalable data pipelines and ETL workflows.
• Extract, transform, and load data from multiple sources.
• Write optimized SQL queries for data extraction and transformation.
• Develop data processing solutions using Python.
• Monitor data pipelines and troubleshoot data quality or processing issues.
• Work with data analysts, data scientists, software engineers, and business teams.
• Design and maintain data models and database structures.
• Implement data validation and quality checks.
• Optimize data pipelines for performance and reliability.
• Document data pipelines, processes, and technical solutions.
• Support cloud-based data platforms and data integration projects.
• Participate in Agile development and code reviews.

Required Qualifications

• 1-3 years of professional Data Engineering or related experience.
• Strong proficiency in Python and SQL.
• Experience with ETL/ELT processes and data pipelines.
• Experience working with relational databases.
• Knowledge of data modeling and database concepts.
• Familiarity with Git and software development practices.
• Strong analytical and problem-solving skills.
• Bachelor's degree in Computer Science, Information Technology, Engineering, or related field preferred.

Preferred Skills

• Python
• SQL
• ETL / ELT
• Data Pipelines
• Data Modeling
• PostgreSQL / MySQL

Equal Opportunity Employer

We are an equal opportunity employer.

All aspects of employment including the decision to hire, promote, discipline, or discharge, will be based on merit, competence, performance, and business needs.

We do not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical condition, pregnancy, genetic information, gender, sexual orientation, gender identity or expression, national origin, citizenship/ immigration status, veteran status, or any other status protected under federal, state, or local law.