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Data Engineer skills for your resume and career

Updated January 8, 2025
5 min read
Quoted Experts
Kazim Sekeroglu Ph.D.,
Daniel Asamoah Ph.D.
Data Engineer Example Skills

Some of the most important hard skills a data engineer can demonstrate on their resume are data analysis and data visualization because these skills make up a large bulk of the job. It's also important for data scientists to have experience working with Cloud software and other key softwares, and programming languages such as Scala.


When it comes to soft skills, data engineers should have strong critical thinking skills above all else. Data engineers need to find solutions and be open to changes in plans, so adaptability skills are also crucial.

Below we've compiled a list of the most critical data engineer skills. We ranked the top skills for data engineers based on the percentage of resumes they appeared on. For example, 12.2% of data engineer resumes contained python as a skill. Continue reading to find out what skills a data engineer needs to be successful in the workplace.

15 data engineer skills for your resume and career

1. Python

Python is a widely-known programming language. It is an object-oriented and all-purpose, coding language that can be used for software development as well as web development.

Here's how data engineers use python:
  • Developed fuzzy-text matching program in Python to identify and eliminate redundancy on county instruments.
  • Developed data quality portal using Python scripting.

2. Java

Java is a widely-known programming language that was invented in 1995 and is owned by Oracle. It is a server-side language that was created to let app developers "write once, run anywhere". It is easy and simple to learn and use and is powerful, fast, and secure. This object-oriented programming language lets the code be reused that automatically lowers the development cost. Java is specially used for android apps, web and application servers, games, database connections, etc. This programming language is closely related to C++ making it easier for the users to switch between the two.

Here's how data engineers use java:
  • Configured and optimized the Cassandra cluster and developed real-time java based application to work along with the Cassandra database.
  • Developed SparkSQL automation components and responsible for modifying java component to directly connect to thrift server.

3. Cloud

Cloud is a server that is accessed over the internet. There are different programs and software that also run on these servers. These clouds can be accessed from anywhere in the world as they are not present in your computer storage, but have their online servers. Cloud consists of data centers all across the world.

Here's how data engineers use cloud:
  • Worked with Amazon Web Services (AWS)cloud infrastructure services and involved in ETL, Data Integration and Migration.
  • Led the capability building exercise for the bank foraying into Big Data with open source MongoDb and on cloud.

4. ETL

Here's how data engineers use etl:
  • Designed ETL architecture and architecture documents and mapping documents.
  • Developed ETL jobs using DataStage to populate dimensional models.

5. Scala

Scala is a modern programming language with multiple paradigms with which common programming models and patterns can be concisely, elegantly, and reliably expressed. Scala was created by Martin Odersky and published the first version in 2003. It combines functional and object-oriented programming in a concise high-level language. Many of Scala's design decisions are aimed at addressing criticism of Java. It interoperates seamlessly with both Java and Javascript. It is strongly seen as a static type language and does not have a primitive data concept.

Here's how data engineers use scala:
  • Used SCALA to store streaming data to HDFS and to implement Spark for faster processing of data.
  • Develop ETL Process using SPARK, SCALA, HIVE and HBASE.

6. Kafka

Kafka is a type of software that which data memory for storage, streaming, and analysis of data. This open-source software is often used to collect extensive data files for real-time data streaming to develop a new feature and create awareness of updates for new consumers or users. One of the most convenient software features is that it is reliable, fast, totally free, and designed for large networks and companies. It can run through various serves and gives them an additional storage capacity.

Here's how data engineers use kafka:
  • Designed and configured Kafka cluster to accommodate heavy throughput messages per second.
  • Created Kafka topics and distributed to different consumer applications.

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7. NoSQL

Here's how data engineers use nosql:
  • Used Cassandra as the NoSQL Database and acquired very good working experience with NoSQL databases.
  • Worked with MongoDB and utilized NoSQL for non-relation data storage and retrieval.

8. Data Lake

Here's how data engineers use data lake:
  • Designed and developed a critical ingestion pipeline to process over 100TB of data into a Data Lake.
  • Created PigLatin Scripts to extract the required data from the large data lake.

9. Visualization

Here's how data engineers use visualization:
  • Programmed BI visualization reports giving insights on patient performance thereby aiding the decision making for clinical drug investigators.
  • Delivered an interactive network visualization framework for quickly responding to and resolving network availability issues and service disruptions.

10. Data Analytics

Here's how data engineers use data analytics:
  • Synthesized and advocated insights, and recommendations from data analytics and modeling.
  • Developed ad-clicks based data analytics, for keyword analysis and insights.

11. Redshift

Here's how data engineers use redshift:
  • Developed migration framework to RedShift DW platform.
  • Designed the production Redshift data warehouse star schema for the proper balance of performance, cost, and flexibility.

12. Data Pipeline

Here's how data engineers use data pipeline:
  • Developed code to create dashboards or reports, enabling executives, technical leads, and product managers to monitor the data pipeline
  • Developed data pipelines to parse raw data to store in partitioned hive tables for reporting and analysis.

13. Power Bi

Here's how data engineers use power bi:
  • Created analytical reports/dashboards from multidimensional models to identify critical KPIs utilizing Power BI.
  • Power BI (Training) Setup and configured always on instances.

14. EMR

Here's how data engineers use emr:
  • Worked on Spark SQL and DataFrames for faster execution of Hive queries using Spark and AWS EMR.
  • Analyzed converted legacy EMR (Electronic Medical Record) data for Epic EMR compatibility and accuracy.

15. Azure

Here's how data engineers use azure:
  • Worked with the windows PowerShell and Azure scheduler to automate the data ingestion and transformation jobs on daily and monthly schedules.
  • Prepare and Present the Metrics for the Team utilization and Environment status in PowerBI, Power Point and SQL Azure.
top-skills

What skills help Data Engineers find jobs?

Tell us what job you are looking for, we’ll show you what skills employers want.

What skills stand out on Data Engineer resumes?

Kazim Sekeroglu Ph.D.

Assistant Professor, Computer Science, Southeastern Louisiana University

Having hands-on experience with data science projects to solve real-world problems by using state-of-the-art data science libraries.

What soft skills should all Data Engineers possess?

Daniel Asamoah Ph.D.

Associate Professor and Interim Chair, Wright State University

Communication skills, self-driven, ability to work in an unstructured environment.

What hard/technical skills are most important for Data Engineers?

Daniel Asamoah Ph.D.

Associate Professor and Interim Chair, Wright State University

Statistics, programming in Python and R.

What Data Engineer skills would you recommend for someone trying to advance their career?

Kit Cho

Associate Professor of Psychology, University of Houston - Downtown


Many employment-based websites such as Zippia provide a wealth of information on career-related trends. These websites also, conveniently, include information on the skills required for certain positions. Research the skills required to attain positions for which you are looking to advance in the near future and work on those skills. This will put you in a better position to seek a promotion or a raise.

What type of skills will young Data Engineers need?

Zhixin Wu Ph.D.Zhixin Wu Ph.D. LinkedIn Profile

Associate Professor, DePauw University

Problem solving skills, analytical skills, self-learning ability, and good communication skills.
Do you want to know more?
Read more about what experts have to say about Data Engineer

List of data engineer skills to add to your resume

Data Engineer Skills

The most important skills for a data engineer resume and required skills for a data engineer to have include:

  • Python
  • Java
  • Cloud
  • ETL
  • Scala
  • Kafka
  • NoSQL
  • Data Lake
  • Visualization
  • Data Analytics
  • Redshift
  • Data Pipeline
  • Power Bi
  • EMR
  • Azure
  • Data Analysis
  • Data Quality
  • Data Processing
  • Data Warehouse
  • BI
  • GIT
  • HBase
  • Apache Spark
  • Amazon Web Services
  • Data Warehousing
  • Linux
  • Relational Databases
  • API
  • Extraction
  • SQL Server
  • EC2
  • HDFS
  • Jenkins
  • Data Ingestion
  • Cloud Computing
  • Elasticsearch
  • Snowflake
  • MapReduce
  • Informatica
  • Unix
  • JavaScript
  • Microservices
  • Ssis
  • Apache Kafka

Updated January 8, 2025

Zippia Research Team
Zippia Team

Editorial Staff

The Zippia Research Team has spent countless hours reviewing resumes, job postings, and government data to determine what goes into getting a job in each phase of life. Professional writers and data scientists comprise the Zippia Research Team.

Updated January 8, 2025

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