Data Engineer

Technologies We Work With

At Data Couch, you’ll gain exposure to a wide range of modern tools and technologies, including:

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    Big Data: Apache Spark, Hadoop, Hive, HBase, Pig
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    Cloud Platforms: AWS, GCP, Microsoft Azure
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    Programming: Python, Scala, SQL, PySpark
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    DevOps & Orchestration: Kubernetes, Docker, Jenkins, Terraform
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    Data Engineering Tools: Apache Airflow, Kafka, Flink, NiFi
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    Data Warehousing: Snowflake, Amazon Redshift, Google BigQuery
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    Analytics & Visualization: Power BI, Tableau
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    Machine Learning & MLOps: MLflow, Databricks, TensorFlow, PyTorch
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    Version Control & CI/CD: Git, GitLab CI/CD, CircleCI

  
  Key Responsibilities

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    Design, build, and maintain robust and scalable data pipelines using PySpark
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    Leverage Hadoop ecosystem (HDFS, Hive, etc.) for big data processing
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    Develop and deploy data workflows in cloud environments (AWS, GCP, or Azure)
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    Use Kubernetes to manage and orchestrate containerized data services
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    Collaborate with cross-functional teams to develop integrated data solutions
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    Monitor and optimize data workflows for performance, reliability, and security
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    Follow best practices for data governance, compliance, and documentation