登录查看更多内容

You’re a team leader with an open position for a data engineer. What are the top skills you should look for?

由人工智能和领英社区提供技术支持

Data engineering is a crucial role in any data-driven organization. As a team leader, you want to hire a data engineer who can design, build, and maintain scalable data pipelines, as well as work effectively with other data professionals and stakeholders. But what are the top skills you should look for in a data engineer? Here are some of the most important ones.

此文章中的业界达人

由社区从 14 条内容中精选。了解更多

Ricardo Cácio

Data & AI | Top Data Engineering Voice | Top Data Analytics Voice | Top Business Intelligence Voice | Microsoft and…
Anand Vardhan

Vice President at SMBC

1 Programming and SQL

A data engineer needs to be proficient in at least one programming language, such as Python, Java, or Scala, to write scripts, automate tasks, and perform data analysis. Additionally, a data engineer should master SQL, the standard language for querying and manipulating relational databases. SQL skills are essential for extracting, transforming, and loading (ETL) data from various sources, as well as creating and optimizing data models and schemas.

添加您的观点

Ricardo Cácio

Data & AI | Top Data Engineering Voice | Top Data Analytics Voice | Top Business Intelligence Voice | Microsoft and Databricks Certified Professional
举报内容
In my opinion, the key skills to consider when evaluating candidates for a data engineering role would be: Proficiency in programming languages commonly used in data engineering In-depth knowledge of relational databases (e.g. PostgreSQL, MySQL) and NoSQL databases (e.g. MongoDB, Cassandra), Experience in designing and implementing ETL processes for extracting, transforming and loading data, Proficiency in data modeling concepts and data warehouse design, Familiarity with big data technologies, Experience with data integration tools and platforms, ensuring continuous data flow between systems and understanding data quality best practices and ability to implement data governance processes.

已翻译

赞
Frank Toshioka

Mestre em Desenvolvimento de Tecnologia e Engenheiro Eletricista - Combate às perdas, Gest?o de Medi??es de Fronteira, Gest?o de Consumidores do Mercado Livre, P&D, Gest?o migra??o ao ACL (Mercado Livre de Energia).
举报内容
When hiring a data engineer, look for skills in programming languages (e.g., Python, SQL), proficiency in data modeling and warehousing, expertise in ETL processes and tools (e.g., Apache Spark), and experience with databases. Strong analytical and problem-solving skills, attention to detail, and familiarity with cloud platforms are crucial. Seek candidates with a solid understanding of data security, collaborative teamwork, and effective communication. Adeptness in emerging technologies and continuous learning is an added advantage for a dynamic data engineering role.

已翻译

赞
Yash Bhavsar

Junior Data Engineer at JET2 | Cloud Data Engineer/ Data warehouse | Data Platform |Snowflake| DBT | Microsoft Azure/AWS| SQL| Python
举报内容
As a team leader hiring a data engineer, prioritize candidates with strong programming skills in languages like Python, SQL, or Java. Additionally, look for expertise in data manipulation, extraction, transformation, and loading (ETL), along with experience with databases, data warehousing, and familiarity with big data technologies like Hadoop or Spark.

已翻译

赞
Davinder Pal Singh

Sr. Engineer @ Walmart | ex-Cisco | BITS Pilani | IIIT-B | LJMU | Certified Cloud Software Engineer | Next.js| SpringBoot | Terraform | Azure | GCP | K8s | Python | Java | SQL
举报内容
Other than Python,SQL. One must be aware of Big Data technologies: Hadoop, Hive, MapReduce, Apache Spark, PySpark, some roles require real time data processing using Kafka.

已翻译

赞
Harshit Arvind Barde

Data Engineer | AI & Machine Learning Enthusiast | Python, Power BI, AWS, GCP | University of Michigan
举报内容
Programming Language: Proficient in Python, Java, or Scala for scripting, task automation, and data analysis. SQL Mastery: Skilled in SQL for querying and manipulating relational databases, essential for ETL processes, data modeling, and schema optimization.

已翻译

赞

加载更多内容

2 Data warehousing and cloud computing

A data engineer should also have experience with data warehousing and cloud computing platforms, such as Amazon Web Services (AWS), Google Cloud Platform (GCP), or Microsoft Azure. Data warehousing involves storing and organizing large amounts of structured and semi-structured data in a centralized repository that supports fast and complex queries. Cloud computing offers various services and tools for data engineering, such as storage, processing, analytics, and machine learning. A data engineer should be familiar with the best practices and architectures for building and managing data warehouses and cloud-based data pipelines.

添加您的观点

Omid Karami

Senior Data Engineer | MSc. Data Science and Intelligent Automation
举报内容
A skilled data engineer must have extensive experience with dimensional modeling and managing structured and unstructured data. Nowadays, unstructured data is very popular, and the capability to transfer and load this type of data to a warehouse or data lake is crucial. Knowledge of orchestration and automation of data flows is essential.

已翻译

赞
Harshit Arvind Barde

Data Engineer | AI & Machine Learning Enthusiast | Python, Power BI, AWS, GCP | University of Michigan
举报内容
A data engineer needs experience with data warehousing and cloud computing platforms like AWS, GCP, or Azure. Data warehousing involves storing and organizing large amounts of data for fast querying. Cloud computing provides tools for data engineering, storage, processing, analytics, and machine learning. Familiarity with best practices for building and managing data warehouses and cloud-based data pipelines is essential.

已翻译

赞

3 Data quality and testing

A data engineer should care about data quality and testing, as they affect the reliability and accuracy of the data products and insights. Data quality refers to the degree to which data meets the expectations and requirements of the users and consumers. A data engineer should be able to identify, monitor, and resolve data quality issues, such as missing, inconsistent, or inaccurate data. Testing involves verifying and validating the functionality and performance of the data pipelines, systems, and applications. A data engineer should be able to apply testing frameworks and methods, such as unit testing, integration testing, and load testing, to ensure the data engineering solutions are robust and scalable.

添加您的观点

Harshit Arvind Barde

Data Engineer | AI & Machine Learning Enthusiast | Python, Power BI, AWS, GCP | University of Michigan
举报内容
Data quality and testing are crucial for reliable and accurate data products. A data engineer must address issues like missing or inaccurate data. Testing, including unit and integration testing, ensures robust and scalable data engineering solutions.

已翻译

赞
Omid Karami

Senior Data Engineer | MSc. Data Science and Intelligent Automation
举报内容
An innovative data engineer must comply with data privacy regulations and organization standards. They must also follow and understand business requirements and data governance and compliance standards and ensure that all data and analytics products are appropriately cataloged and documented.

已翻译

赞

4 Communication and collaboration

A data engineer should also have strong communication and collaboration skills, as they work closely with other data professionals and stakeholders. Communication skills involve the ability to explain and document the data engineering processes and outcomes, as well as to understand and translate the business needs and goals. Collaboration skills involve the ability to work effectively and efficiently with others, such as data analysts, data scientists, software engineers, and product managers, to deliver data-driven solutions. A data engineer should be able to use collaboration tools and platforms, such as Git, GitHub, or Bitbucket, to manage and share code, as well as to follow agile and scrum methodologies to organize and prioritize tasks.

添加您的观点

Anand Vardhan

Vice President at SMBC
举报内容
Data engineers work closely with cross-functional teams, including data scientists, analysts, and business stakeholders. Look for candidates who have strong communication skills, can collaborate effectively, and can translate technical concepts to non-technical stakeholders.

已翻译

赞

5 Learning and curiosity

A data engineer should also have a learning and curiosity mindset, as they face new challenges and opportunities in the fast-changing data landscape. Learning skills involve the ability to acquire and update knowledge and skills, as well as to learn from feedback and mistakes. Curiosity skills involve the ability to explore and experiment with new data sources, technologies, and methods, as well as to ask relevant and insightful questions. A data engineer should be able to demonstrate their learning and curiosity skills by taking online courses, attending workshops and conferences, reading blogs and books, and participating in communities and forums.

添加您的观点

6 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?

添加您的观点

加载更多内容

Data Engineering

+ 关注

给文章评分

我们借助人工智能创建了此文章。您认为这篇文章怎么样？

很棒不太好

举报此文章

查看全部

You’re a team leader with an open position for a data engineer. What are the top skills you should look for?

1

2

3

4

5

6

1 Programming and SQL

2 Data warehousing and cloud computing

3 Data quality and testing

4 Communication and collaboration

5 Learning and curiosity

6 Here’s what else to consider

Data Engineering

给文章评分

感谢您的反馈

更多Data Engineering相关文章

更多相关阅读内容

You’re a team leader with an open position for a data engineer. What are the top skills you should look for?

1

2

3

4

5

6

1 Programming and SQL

2 Data warehousing and cloud computing

3 Data quality and testing

4 Communication and collaboration

5 Learning and curiosity

6 Here’s what else to consider

Data Engineering

给文章评分

感谢您的反馈

查看其他技能