TheCorporate
Overview
Data Engineer. 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. 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
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Data Engineer. 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. 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
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