Data Engineer (Remote - US) at Jobgether

Remote - United States

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This position is posted by Jobgether on behalf of a partner company. We are currently looking for a Data Engineer in United States. As a Data Engineer, you will play a pivotal role in designing, building, and maintaining robust, secure, and scalable data infrastructure that powers analytics, reporting, and advanced data science initiatives. You will work closely with cross-functional teams to ensure high-quality, reliable, and accessible data, enabling data-driven decisions across the organization. This role offers exposure to both batch and real-time data processing, modern cloud platforms, and cutting-edge big data technologies. You will have the opportunity to implement best practices in data governance, security, and pipeline orchestration, while continuously exploring innovative tools and frameworks. Your contributions will directly influence the organization's ability to leverage data as a strategic asset.

Requirements

Skills

  • Python
  • Java
  • Scala
  • SQL
  • Airflow
  • dbt
  • Kafka
  • Apache Spark
  • Databricks
  • Flink
  • AWS
  • Azure
  • Google Cloud
  • Data Lake
  • Lakehouse
  • Data Warehouse
  • Docker
  • Kubernetes
  • Data Modeling
  • Metadata Management
  • Data Lineage
  • CI/CD
  • Snowflake
  • Redshift
  • BigQuery
  • Delta Lake
  • Analytical Skills
  • Problem-Solving
  • Communication Skills
  • Collaboration
  • Infrastructure-as-Code
  • Machine Learning Data Pipelines
  • Data Governance Frameworks
  • GDPR
  • HIPAA
  • FedRAMP

Languages

  • English

Responsibilities

  • Design, develop, and optimize ETL/ELT processes for structured and unstructured datasets
  • Build and maintain data pipelines integrating multiple internal and external data sources
  • Implement data quality, validation, and monitoring processes to ensure reliable enterprise data
  • Support both real-time streaming and batch data processing pipelines
  • Collaborate with data architects, analysts, and scientists to deliver scalable, high-performing solutions
  • Ensure data security, compliance, and governance standards are met
  • Evaluate and recommend new data engineering tools, techniques, and platforms for continuous improvement

Technologies

PythonJavaScalaSQLAirflowdbtKafkaApache SparkDatabricksFlinkAWSAzureGoogle CloudDockerKubernetesSnowflakeRedshiftBigQueryDelta LakeTerraformCloudFormation

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