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Cloud Engineer / Data Engineer

NET2ASPIRE LLCUnited States🇺🇸United States

Quick overview

SeniorityMid Senior
Work modeHybrid
LocationUnited States
DockerMongoDBMySQLSQLGitApache SparkAWSETLScrumSnowflakeAirflowApacheBigQueryData PipelineDatabricksGoogle CloudHadoopJavaJenkinsKafkaPythonRedshiftTerraformAzurePostgreSQLSQL ServerAgileLinuxAzure Data FactoryIAM

Job description

We are seeking a motivated and detail-oriented Cloud Engineer / Data Engineer to join our technology team. The ideal candidate will assist in designing, developing, implementing, and maintaining cloud-based infrastructure and data processing solutions. This role involves working with cloud platforms, data pipelines, databases, automation tools, and distributed systems to support business intelligence and data-driven applications.

Key Responsibilities

  • Assist in designing, deploying, and maintaining cloud-based infrastructure using AWS, Azure, or Google Cloud Platform (Google Cloud Platform).

  • Develop and maintain data pipelines for collecting, processing, transforming, and storing large datasets.

  • Work with structured and unstructured data across multiple data sources.

  • Support cloud storage, computing, networking, and database services.

  • Build and maintain ETL/ELT workflows for data integration and transformation.

  • Implement data processing solutions using Python, SQL, and Spark.

  • Assist in managing data warehouses, data lakes, and cloud databases.

  • Monitor cloud infrastructure, data pipelines, and system performance.

  • Collaborate with software developers, data analysts, and engineering teams.

  • Automate data workflows and infrastructure provisioning.

  • Troubleshoot data quality, pipeline failures, and cloud infrastructure issues.

  • Maintain technical documentation and follow data security and governance practices.

Required Technical Skills

Skill Category

Technologies

Cloud Platforms

AWS, Azure, Google Cloud (Google Cloud Platform)

Programming

Python, SQL, Java

Data Processing

Apache Spark, PySpark, Hadoop

ETL/ELT Tools

Azure Data Factory, AWS Glue, Informatica

Databases

MySQL, PostgreSQL, SQL Server, MongoDB

Data Warehousing

Snowflake, Amazon Redshift, Google BigQuery

Cloud Storage

Amazon S3, Azure Blob Storage, Google Cloud Storage

Data Pipeline

Apache Airflow, Kafka, Databricks

DevOps & Automation

Git, Docker, Jenkins, Terraform

Operating Systems

Linux, Windows

Educational Qualifications

  • Bachelor's or Master's degree in Computer Science, Information Technology, Data Science, Software Engineering, or a related field.

  • Entry Level Candidates and entry-level candidates with relevant academic projects, internships, or hands-on technical experience are encouraged to apply.

Preferred Qualifications

  • Basic understanding of cloud architecture and distributed computing.

  • Familiarity with ETL/ELT processes and data integration.

  • Knowledge of data modeling and database optimization.

  • Understanding of data lakes and data warehouse concepts.

  • Exposure to cloud security, IAM, and access management.

  • Familiarity with Agile and Scrum methodologies.

  • Understanding of data governance and data quality practices.

Key Competencies

  • Analytical and problem-solving skills.

  • Strong programming and SQL fundamentals.

  • Understanding of cloud computing concepts.

  • Data processing and troubleshooting abilities.

  • Good communication and teamwork.

  • Ability to work in a collaborative technical environment.

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