Machine Learning Engineer (The AI Innovator)

Posted 2024-11-07

💎 Seniority level: Middle, 3+ years

📍 Location: United States

🏢 Company: Unreal Gigs

⏳ Experience: 3+ years

🪄 Skills: AWSPythonSQLApache AirflowETLGCPJavaKafkaStrategyAirflowApache KafkaAzureData engineeringData StructuresNosql

Experience with cloud data platforms such as AWS, GCP, or Azure.
Proficiency in Python, Java, or Scala for building data pipelines.
Proven ability to maintain and optimize ETL processes using orchestration tools like Apache Airflow or Luigi.
Strong SQL skills and experience with relational and NoSQL databases.
Excellent problem-solving skills and ability to resolve data challenges.
Bachelor’s or Master’s degree in Computer Science, Data Engineering, or related field, or equivalent experience.

Develop and maintain data pipelines to support data ingestion, transformation, and integration using cloud technologies.
Architect and maintain data lakes and data warehouses using cloud-based solutions like BigQuery, Redshift, or Snowflake.
Work closely with data scientists, analysts, and business stakeholders to align data solutions with business goals.
Implement processes for data validation and ensure the quality of data through robust testing.
Build and automate ETL workflows for efficient data integration.
Use monitoring tools to maintain system health and track data system performance.

Posted 2024-11-07

📍 United States

🏢 Company: Unreal Gigs

Experience with cloud data platforms such as AWS, GCP, or Azure.
Proficiency in programming languages like Python, Java, or Scala.
Ability to manage and optimize ETL processes with orchestration tools.
Strong skills in writing complex SQL queries and working with relational and NoSQL databases.
Bachelor's or Master's degree in Computer Science, Data Engineering, or related field.
Certifications in cloud data engineering are a plus.
3+ years of experience in data engineering and cloud-based data systems.
Experience with real-time data processing frameworks is advantageous.
Familiarity with containerization and microservices architecture is a plus.

Develop and maintain data pipelines for data ingestion, transformation, and integration using cloud technologies.
Architect and maintain data lakes and data warehouses for performance and scalability.
Collaborate with data scientists, analysts, and business stakeholders to align data solutions with business goals.
Implement processes for data validation, error handling, and consistency checks.
Build and automate ETL workflows to support efficient data integration and reporting.
Use monitoring tools to track the performance of data systems and proactively resolve issues.
Implement strategies for efficient resource allocation and cost-effective data processing.

AWSPythonSQLApache AirflowETLGCPJavaKafkaStrategyAirflowApache KafkaAzureData engineeringData StructuresNosql

Posted 2024-11-07

🔧 Requirements