Job Description


Job Overview

  • Job ID:

    J54498

  • Job Title:

    Data Engineer

  • Location:

    Dallas, TX

  • Duration:

    12 Months + Extension

  • Domain Exposure:

    Manufacturing

  • Client:

    To Be Discussed Later

  • Employment Type:

    W-2, 1099, C2C

  • Work Authorization:

    US Citizen, Green Card, H-1B, OPT-EAD, CPT, Other

Job Title: Data Engineer

Location: Dallas, TX

Duration: 12 Months + Extension

Bill Rate: $84/hr C2C

Job Type: W-2, 1099, C2C

Work Authorization: US Citizen, Green Card, OPT-EAD, CPT, H-1B, H4-EAD, Other

Position Overview:

The Data Engineer will build, maintain, and optimize scalable data platforms and pipelines to support enterprise analytics and business intelligence initiatives. This role focuses on data integration, transformation, processing, and cloud-based data architecture while ensuring data quality, reliability, and performance.

Technical Skills & Data Platform Expertise:

  • Strong programming experience with Python, SQL, and PySpark.

  • Hands-on experience with ETL/ELT development and data pipeline architecture.

  • Knowledge of Apache Spark, Hadoop, and distributed data processing.

  • Experience with cloud data platforms such as AWS, Azure, or Google Cloud.

  • Familiarity with Snowflake, Databricks, Amazon Redshift, or Google BigQuery.

  • Experience with data orchestration tools such as Apache Airflow, Azure Data Factory, or AWS Glue.

  • Strong understanding of relational and NoSQL databases.

  • Knowledge of data modeling, data warehousing, and dimensional modeling.

  • Experience with Kafka or other streaming technologies is preferred.

  • Familiarity with Git, Docker, Kubernetes, and CI/CD pipelines.

  • Understanding of data governance, metadata management, and data security.

Data Engineering & Delivery Responsibilities:

  • Design, develop, and maintain scalable ETL/ELT data pipelines.

  • Build data ingestion and transformation workflows from multiple sources.

  • Process large datasets using Python, SQL, PySpark, and Spark.

  • Develop and optimize data warehouse and lakehouse solutions.

  • Implement data validation, reconciliation, and quality checks.

  • Integrate structured and unstructured data from enterprise systems.

  • Optimize query performance and improve data pipeline efficiency.

  • Monitor pipeline execution, troubleshoot failures, and resolve data issues.

  • Implement data security, governance, and access-control standards.

  • Collaborate with data scientists, analysts, architects, and business stakeholders.

Professional Experience & Core Competencies:

  • 5+ years of experience in data engineering or big data development.

  • Strong hands-on experience building and supporting production data pipelines.

  • Experience working with cloud-based data platforms and enterprise databases.

  • Understanding of distributed computing and data processing frameworks.

  • Strong analytical, debugging, and problem-solving abilities.

  • Experience working in Agile development environments.

Educational Background & Preferred Certifications:

  • Bachelor's degree in Computer Science, Information Technology, Data Engineering, or a related field.

  • Master's degree is preferred.

  • Certifications in AWS, Azure, Google Cloud, Snowflake, or Databricks are an advantage.


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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.