Data Engineer

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TheCorporate
55.00 - 65.00 USD / Hour
  • IT
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Job Title: Data Engineer

About The Role We are seeking a skilled Data Engineer to join our team and help design, build, and optimize data pipelines and architectures that power business intelligence, analytics, and data-driven decision-making. This role is fully remote within the United States.

The ideal candidate has strong experience in building scalable data systems, working with large datasets, and collaborating with cross-functional teams including analysts, data scientists, and software engineers.

Key Responsibilities

  • Design, develop, and maintain scalable ETL/ELT pipelines for structured and unstructured data.
  • Build and optimize data architectures to support analytics, reporting, and machine learning initiatives.
  • Work with stakeholders to define data requirements and deliver solutions that meet business needs.
  • Ensure data quality, integrity, and governance across systems and pipelines.
  • Implement best practices for data modeling, warehousing, and storage solutions.
  • Monitor, troubleshoot, and optimize data workflows for performance and reliability.
  • Collaborate with engineering teams to integrate data solutions into applications and platforms.
  • Stay updated on emerging data technologies and recommend improvements to existing processes.

Qualifications Required:

  • Bachelor’s degree in Computer Science, Information Systems, Engineering, or related field (or equivalent experience).
  • 3+ years of experience as a Data Engineer or in a related data-focused role.
  • Proficiency in SQL and data modeling.
  • Hands-on experience with cloud platforms (AWS, Azure, or GCP).
  • Strong knowledge of data warehousing tools (e.g., Snowflake, Redshift, BigQuery).
  • Experience with ETL tools (e.g., dbt, Airflow, Talend, Informatica).
  • Proficiency in at least one programming language (Python, Java, or Scala).
  • Familiarity with big data frameworks (Spark, Hadoop, Kafka).

Preferred

  • Experience with containerization (Docker, Kubernetes).
  • Knowledge of data governance and security best practices.
  • Exposure to machine learning pipelines and data science workflows.
  • Strong communication skills with the ability to work across technical and non-technical teams.

Skills: data,machine learning,data modeling,pipelines