Job Description
Job Description
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
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Design, develop, and maintain scalable ETL/ELT pipelines for structured and unstructured data.
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Build and optimize data architectures to support analytics, reporting, and machine learning initiatives.
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Work with stakeholders to define data requirements and deliver solutions that meet business needs.
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Ensure data quality, integrity, and governance across systems and pipelines.
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Implement best practices for data modeling, warehousing, and storage solutions.
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Monitor, troubleshoot, and optimize data workflows for performance and reliability.
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Collaborate with engineering teams to integrate data solutions into applications and platforms.
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Stay updated on emerging data technologies and recommend improvements to existing processes.
Qualifications
Required:
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Bachelor’s degree in Computer Science, Information Systems, Engineering, or related field (or equivalent experience).
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3+ years of experience as a Data Engineer or in a related data-focused role.
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Proficiency in SQL and data modeling.
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Hands-on experience with cloud platforms (AWS, Azure, or GCP).
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Strong knowledge of data warehousing tools (e.g., Snowflake, Redshift, BigQuery).
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Experience with ETL tools (e.g., dbt, Airflow, Talend, Informatica).
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Proficiency in at least one programming language (Python, Java, or Scala).
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Familiarity with big data frameworks (Spark, Hadoop, Kafka).
Preferred:
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Experience with containerization (Docker, Kubernetes).
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Knowledge of data governance and security best practices.
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Exposure to machine learning pipelines and data science workflows.
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Strong communication skills with the ability to work across technical and non-technical teams.
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