Cloud Data Engineer Career

Functional Skills

Functional Skills are essential skills that help individuals perform tasks effectively in everyday life, work, and education.

Data Warehousing

Cloud Storage Solutions

Data Integration

Big Data Technologies

SQL and NoSQL Databases

Data Modeling

Cloud Platform Knowledge

Programming Skills

Data Governance and Security

Data Analysis and Visualization

DevOps Practices

Soft Skills

Communication, teamwork, and critical thinking to ensure seamless project execution.

Technical Skills

Technical Skills are specialized abilities and knowledge needed to perform specific tasks or functions.

Cloud Computing Platforms (AWS, Azure, GCP)

Data Warehousing Solutions

ETL Tools (Informatica, Apache NiFi, Talend)

Big Data Technologies (Hadoop, Spark)

SQL and NoSQL Databases

Programming Languages (Python, Java, Scala)

Data Modeling

Data Governance and Security

DevOps Practices (CI/CD, Infrastructure as Code)

Data Visualization (Tableau, Power BI)

Cloud-Native Data Streaming (Kafka, Kinesis)

Duties and Responsiblities

Task

95%

Design and implement cloud-based data warehouses and data lakes on platforms like AWS, Azure, or GCP.

92%

Develop and maintain data pipelines using tools like Apache Kafka, Apache Spark, or Azure Data Factory.

90%

Ensure data quality and integrity by implementing validation rules and monitoring data flows.

88%

Optimize data storage and retrieval processes for performance and cost-efficiency.

85%

Collaborate with data scientists and analysts to understand their data requirements and provide solutions.

82%

Implement data security measures, including encryption and access controls, to protect sensitive data.

80%

Automate data engineering tasks using scripting languages like Python and infrastructure-as-code tools.

78%

Monitor and troubleshoot data pipeline issues, ensuring minimal downtime and data loss.

75%

Stay updated with the latest cloud data engineering technologies and best practices.

72%

Document data engineering processes and create knowledge base articles for team members.

70%

Participate in code reviews and contribute to the improvement of data engineering standards.

Work Activities

95%

Architect robust data pipelines for efficient data ingestion, transformation, and loading into cloud data warehouses.

92%

Design and implement optimal data models within cloud-based data warehouses like Snowflake or BigQuery.

90%

Develop and maintain ETL (Extract, Transform, Load) processes using tools like Apache Spark or cloud-native services.

88%

Manage and optimize cloud data warehouse performance, ensuring data quality, security, and availability.

85%

Implement and maintain data security measures, including encryption, access controls, and compliance with data privacy regulations.

82%

Build and manage data lakes on cloud platforms like AWS S3 or Azure Data Lake Storage for storing unstructured and semi-structured data.

80%

Establish and enforce data governance policies and procedures to ensure data quality, consistency, and compliance.

78%

Maintain expertise in cloud platforms (AWS, Azure, GCP) and their data-related services.

75%

Optimize data pipelines and queries for performance and scalability in cloud environments.

72%

Collaborate with data scientists, analysts, and other stakeholders to understand data requirements and deliver solutions.

70%

Automate data-related tasks and processes using scripting languages and cloud automation tools.

Detailed Work Profile

Interests