Data Engineer

Data Engineer Resume Keywords and Skills (Hard Skills)

Here are the keywords and skills that appear most frequently on recent Data Engineer job postings. In other words, these are the most sought after skills by recruiters and hiring managers. Go to Sample Templates ↓ below to see how to include them on your resume.

Remember that every job is different. Instead of including all keywords on your resume, identify those that are most relevant to the job you're applying to. Use the free Targeted Resume tool to help with this.

Choose a category
  • Apache Spark
  • Amazon Web Services (AWS)
  • Data Engineering
  • Hadoop
  • Python (Programming Language)
  • Scala
  • Extract, Transform, Load (ETL)
  •  Find out what your resume's missing
  • Apache Kafka
  • Big Data
  • Docker Products
  • Machine Learning
  • Hive
  • SQL
  • Data Warehousing
  • Data Science
  • Git
  • PostgreSQL
  • Apache Airflow
  • Java
  • Data Analysis
  • PySpark
  • Tableau
  • Amazon Redshift
  • Big Data Analytics
  • MySQL

  •   Show full list

Resume Skills: Database

Resume Skills: Big Data

  • Hadoop
  • Spark
  • Hive
  • Pig
  • Kafka
  • Redis
  • Presto
  • Oozie
  • Apache Spark
  • MapReduce
  • AWS Glue
  • Apache Hadoop
  • Sqoop
  • Flume
  • TensorFlow
  • PyTorch
  • Scikit-learn
  • AWS
  • Azure
  • Google Cloud
  • Databricks
  • Elasticsearch
  • Storm
  • AWS (S3, EC2, EMR, Lambda, RDS, Redshift)
  • MS Azure
  • Docker
  • Kubernetes
  •  Match your resume to these skills

Resume Skills: Programming

  • Java
  • Python
  • R
  • SQL
  • Scala
  • Go
  • Shell Scripts
  • SAS
  • C#
  • C++
  • Shell scripting
  • Python (Pandas, NumPy)
  • Perl
  • Ruby
  • JavaScript
  • NoSQL databases (MongoDB, Cassandra)
  •  Match your resume to these skills

Resume Skills: Cloud

  • Hadoop
  • Spark
  • AWS
  • Azure
  • Google Cloud
  • Databricks
  • Hive
  • Pig
  • Elasticsearch
  • BigQuery
  • AWS (S3, EC2, EMR, Redshift)
  • Google Cloud Platform
  • Microsoft Azure
  • IBM Cloud
  •  Match your resume to these skills

Resume Skills: Data Processing & Analysis

Resume Skills: Data Visualization Tools

Resume Skills: Machine Learning Tools

Resume Skills: Data Analytics Tools

Resume Skills: Data Modeling

Resume Skills: Data Engineering Tools

Resume Skills: Data Warehousing

  Does your resume contain all the right skills? Paste in your resume in the AI Resume Scan ↓ section below and get an instant score.

Compare Your Resume To These Data Engineer Skills (ATS Scan)

Paste your resume below and our AI will identify which keywords are missing from your resume from the list above (and what you need to include). Including the right keywords will help you get past Applicant Tracking Systems (i.e. resume screeners) which may scan your resume for keywords to see if you're a match for the job.

Sample Data Engineer Resume Examples: How To Include These Skills

Add keywords directly into your resume's work experiences, education or Skills section, like we've shown in the examples below. Use the examples below as inspiration.

Select a free resume example
Your Name
Data Engineer
City, Country  •  (123) 456-789  •  [email protected]  •
Resume Worded April 2019 - Present
Senior Data Engineer
Engineered and launched an Apache Kafka based real-time data processing pipeline, which processed 7 TB per day and reduced latency by 65%
Executed advanced data analytics using PySpark, improving customer targeting strategy by 40%
Collaborated with a cross-functional team of data scientists and machine learning engineers to build predictive models, increasing sales by 15%
Designed and implemented Docker-based deployment workflows, improving continuous integration/continuous deployment (CI/CD) processes by 30%
Architected and maintained PostgreSQL databases, resulting in 50% improvement in the query response time July 2016 - March 2019
Data Engineer
Conducted ETL operations using Apache Spark and Hadoop, shortening data preparation time by 60%
Enhanced data warehousing strategy with data modeling techniques, leading to 20% improvement in data interpretation
Optimized SQL queries with efficient schema design, decreasing data redundancy by 25%
Developed and managed AWS Redshift clusters to handle massive sets of raw data, leading to improved system performance
Facebook April 2014 - June 2016
Junior Data Engineer
Assisted in data cleaning and pre-processing with Python scripts, driving up data accuracy by 85%
Contributed to the development of automated ETL jobs using Apache Airflow, saving 10 hours per week
Performed data analyses using SQL, providing insightful reports to the business development team
Resume Worded Institute May 2019
Certified Data Management Professional (CDMP) - Mastery Level
Focused on data governance, data stewardship, and data quality
Resume Worded University May 2014
Master of Science in Data Science
Specialization in statistical methods, computation, and information science
Programming Languages: Python, R, SQL, Java, Scala, Shell Scripts
Big Data Technologies: Apache Spark, Hadoop, Hive, Kafka, Pig, MapReduce
Database Management: PostgreSQL, Oracle DB, MongoDB, MySQL, NoSQL
Data Visualization Tools: Tableau, Power BI, Matplotlib, Seaborn
Certifications: Google Cloud Certified - Professional Data Engineer, AWS Certified Big Data - Specialty
Publications: Authored 'The Data Engineer’s Toolkit: Streamlining Data Pipeline', Published in Data Science Weekly
Projects: Designed and implemented a high-volume data ingestion pipeline for, contributing to a 20% increase in data efficiency
Awards: 'Data Innovation Award', Facebook, 2016
Your Name
Data Analyst
City, Country  •  (123) 456-789  •  [email protected]  •
EXPERIENCE January 2019 - Present
Senior Data Analyst
Employed machine learning models to predict customer churn, resulting in a 20% reduction
Performed A/B testing and statistical analysis in Python, increasing website conversion rates by 15%
Used SQL to query large-scale databases, optimizing data extraction and improving report generation speed by 25%
Created interactive dashboards using Tableau, enhancing data visualization and business decision making
Audited data for data quality and consistency, reducing errors by 85%
Collaborated with business stakeholders to understand business problems, deliver insights, and drive data-driven decision making
Microsoft June 2014 - December 2018
Data Analyst
Conducted deep data analyses using R, leading to the discovery of key trends and insights
Implemented ETL processes, improving data reliability and efficiency by 30%
Created compelling visualizations of quantitative information using PowerBI, leveraging storytelling to interpret patterns and trends
Resume Worded March 2012 - May 2014
Junior Data Analyst
Assisted in the development of data quality measures and data cleansing rules, leading to a 20% increase in data accuracy
Analyzed large data sets using statistical software like SAS, improving data processing times
Resume Worded Institute August 2016
Master of Science in Data Analytics
Focus on Applied Statistics and Predictive Modeling
Resume Worded University May 2012
Bachelor of Science in Computer Science
Minors in Mathematics and Business Analytics
Awards:Dean's List 2012 (Top 10%)
Programming Languages: Python, R, SQL, SAS, Java, C#
Data Analytics Tools: Tableau, Power BI, Excel, SSAS, Google BigQuery, AWS Redshift
Database Management Systems: Oracle, MySQL, PostgreSQL, MongoDB, MS SQL Server
Big Data & Machine Learning Frameworks: Hadoop, Apache Spark, TensorFlow, PyTorch, Scikit-learn
Certifications: SAS Certified Data Scientist, Google Analytics Certified
Professional Development: Attended 'Data Innovation Summit', 'Microsoft Ignite Tech Conference'
Projects: Created predictive models for customer churn analysis, Enhanced data reporting processes resulting in 20% faster decision making
Publications & Presentations: Published 'The Power of Data Analytics in Decision-Making' in 'Data Analysts Monthly'
Your Name
Data Scientist
City, Country  •  (123) 456-789  •  [email protected]  •
Microsoft June 2016 - Present
Data Scientist
Utilized machine learning to build predictive models, resulting in smarter business decision making and a 18% increase in revenue
Leveraged advanced statistical analysis to identify key performance indicators, leading to enhanced business strategy
Devised and implemented novel Deep Learning algorithms using TensorFlow, optimizing data interpretation and pattern recognition
Worked closely with the data engineering team to implement a scalable big data infrastructure
Improved the accuracy of recommender systems by implementing collaborative filtering algorithm, increasing user engagement by 35% January 2014 - May 2016
Junior Data Scientist
Implemented data analysis workflows and machine learning models in Python and R
Created data visualizations and statistical reports to communicate findings to non-technical stakeholders
Assisted in the development of a predictive model to assess customer life value, driving revenue growth
Resume Worded June 2013 - December 2013
Data Analyst Intern
Managed and analyzed large datasets using SQL, supporting business operations
Assisted in the application of statistical methods to assess the impact of marketing campaigns
Conducted data cleaning and preprocessing, increasing data accuracy by 15%
Resume Worded Academic Center May 2016
Master of Science in Data Science
Emphasis on Statistical Programming, Big data computing and Algorithm Designs
Resume Worded University May 2014
Bachelor of Engineering - Computer Science
Minors in Mathematics and Statistics
Awarded distinction for final year project on 'Predictive Analytics using Machine Learning'
Programming Languages: Python (Advanced), R (Advanced), SQL (Advanced), Java (Intermediate)
Big Data and Cloud Platforms: Hadoop, Spark, AWS, Azure, Google Cloud, Databricks, Hive, Pig, Elasticsearch
Machine Learning and Data Visualization: scikit-learn, TensorFlow, Keras, Matplotlib, Seaborn, ggplot
Databases: MySQL, MongoDB, PostgreSQL, Oracle, SQLite
Certifications: Certified Data Scientist – IBM, Six Sigma Green Belt
Conferences & Trainings: Attended Data Science Global Impact Challenge (2018), Completed Machine Learning Training at Coursera (2018)
Publications: Published a research paper titled 'Enhanced Algorithm Design in Predictive Analytics' in Journal of Data Science (2017)
Projects: Developed a predictive model for customer churn analysis which improved customer retention by 15%
Your Name
Data Warehouse Engineer
City, Country  •  (123) 456-789  •  [email protected]  •
Resume Worded February 2019 - Present
Senior Data Warehouse Engineer
Revamped data integration strategy with SSIS, leading to a 40% boost in system throughput.
Employed data warehousing techniques to cleanse and standardize datasets, reducing reporting errors by 35%.
Utilized Informatica and Oracle Database to update ETL processes, enhancing report access time by 25%.
Influenced data warehouse design, resulting in 45% improvement in query performance.
Executed comprehensive requirements analysis, leading to the creation of tailored SQL queries and optimizing database accessibility.
Amazon Web Services May 2015 - January2019
Data Warehouse Developer
Implemented 20+ complex SQL and PL/SQL scripts to automate ETL processes, saving 15 hours weekly.
Employed SSIS to transport data across multiple databases, reducing potential for transfer errors by 30%.
Incorporated Transact-SQL (T-SQL) into system queries, speeding up data mining efforts by 20%.
Developed an efficient data model, resulting in a 10% improvement in BI reporting performance.
Microsoft November 2011 - May 2015
ETL Developer
Spearheaded the development and deployment of ETL workflows with SSIS, leading to a 25% increase in the data transfer rate.
Utilized PL/SQL for complex data transformation tasks, ultimately enhancing system productivity by18%.
Resume Worded University January 2013
Master's in Data Science and Engineering
Focus on Applied Machine Learning and Big Data Analytics
Resume Worded Institute May 2011
Bachelor of Technology - Computer Science
Minors in Mathematics
Awards: Dean's List 2011 (Top 10%)
Programming & Scripting: Python, Java, C#, SQL, Shell script, ETL Tools (Informatica)
Databases: Oracle, PostgreSQL, Amazon Redshift, MySQL, SQL Server
Workflow Management: Jenkins, Bamboo, Airflow, Luigi
Big Data Technologies: Hadoop, Spark, MapReduce, Hive, Pig, Apache Flink, Elasticsearch
Certifications: AWS Certified Big Data - Specialty (2021), Oracle Certified Associate (OCA) - Database Administrator (2013)
Courses: Advanced Data Warehouse Design course, Coursera (2018), Advanced Course in Big Data on Cloud, Coursera (2021)
Leadership & Volunteering: Organizer, Resume Worded Tech Talks (Monthly community meetups), Technical Lead, Code For Cause (2016 - 2019)
Projects: Developed a credit risk prediction model using machine learning techniques, Led the data migration project from SQL Server to Redshift for a retail giant
Your Name
Data Warehouse Consultant
City, Country  •  (123) 456-789  •  [email protected]  •
EXPERIENCE March 2018 - Present
Lead Data Warehouse Consultant
Lead an initiative for restructuring data pipelines utilizing SQL Server Integration Services (SSIS) and Informatica, boosting operational efficiency by 30%.
Deployed data modeling techniques to optimize data loading processes, resulting in 20% less runtime.
Spearheaded quarterly database design reviews, which decreased latencies by 25%.
Applied industry-standard Business Intelligence (BI) practices, causing an augmentation in reporting accuracy by 35%.
Led a team of 8 members and trained them on Hadoop and Hive technologies.
SAP June 2013 - February 2018
Data Consultant
Implemented SQL Server Analysis Services (SSAS) and SQL Server Reporting Services (SSRS) to automate report generation, cutting production time by 22%.
Updated ETL workflows via Informatica and SQL, improving data accuracy by 20%.
Provided critical input during Requirements Analysis phase, improving compliance rates on completed projects by 15%.
Oracle Corporation July 2010 - June 2013
Data Analyst
Used SQL and T-SQL to automate data extraction tasks, which boosted system performance by 15%.
Played a vital role in SDLC by creating accurate data flow diagrams.
Resume Worded Academic Center March 2018
Master in Business Analytics
Graduated on the Dean's List (Top 10%)
Resume Worded University June 2013
Bachelor of Science in Computer Science - Data Science Specialization
Thesis: Predictive Analytics using Machine Learning
Awarded Top Performer in Data Structures and Algorithms
Data Warehousing: ETL, Data Mining, OLAP, OLTP, Star Schema
Programming: Python, Java, SQL, PL/SQL, VB.NET, C#
Databases: SAP HANA, Oracle Database, Microsoft SQL Server
BI Tools: Tableau, PowerBI, Informatica, SAP BusinessObjects
Certifications: Oracle Certified Expert, Java EE 6 Web Component Developer (2019), Certified Data Management Professional (CDMP) (2021)
Leadership & Volunteering: Project Mentor, Girls Who Code (2016 - Present)
Projects: Developed a predictive modelling system for fleet management in Final Year Project (achieved 90% accuracy)
Publications: Co-authored paper on 'Best Practices in Modern Data Warehousing' in Data Science Journal
Your Name
SQL Server Data Warehouse Engineer
City, Country  •  (123) 456-789  •  [email protected]  •
EXPERIENCE March 2017 - Present
Principal SQL Server Data Warehouse Engineer
Designed an advanced SQL Server architecture, reducing server response time by 50%.
Revamped the ETL processes using SSIS and T-SQL, improving data transfer speed by 30%.
Performed data modeling activities, helping reduce storage usage by 25%.
Managed SQL Server Reporting Services (SSRS) for BI solutions, improving report generation speed by 20%.
Utilized cutting-edge data integration frameworks to merge disparate data sources, enhancing overall data quality.
Resume April 2014 - February 2017
SQL Server DBA
Performed database design and optimization, leading to a 30% improvement in data retrieval speeds.
Automated routine database tasks using PL/SQL, saving 10 hours weekly.
Managed SQL Server reporting and analysis services, thereby boosting report accuracy by 15%.
IBM September 2009 - March 2014
SQL Developer
Transformed complex datasets with PL/SQL, enhancing system performance by 20%.
Implemented efficient indexes in SQL Server, improving query response time by 25%.
Resume Worded University August 2013
Master of Science - Database Administration
Thesis: Optimizing SQL Server performance
Resume Worded Academic Center June 2009
Bachelor of Science - Computer Science
Specialization in Database Systems
Awards: Dean’s List 2008 (Top 10%)
Database: SQL Server, Oracle, MySQL, PostgreSQL, MongoDB
Programming Languages: SQL, Python, Java, C#, T-SQL, PL/SQL, R
Tools: SSIS, SSAS, SSRS, Tableau, Power BI, Apache Kafka, Git
Techniques: Data Warehousing, ETL, Data Modeling, Data Mining, Database Design
Certifications: Microsoft Certified: Azure Data Engineer Associate (2020), AWS Certified Database - Specialty (2019)
Awards: Recognized as Top Performer in (2019, 2020)
Projects: Independent project: Developed an automated data pipeline for a ecommerce website using Python and Azure

How do I add skills to a Data Engineer resume?

Review the job posting closely.

Go through the Data Engineer posting you're applying to, and identify hard skills the company is looking for. For example, skills like Data Engineering, Apache Spark and Hadoop are possible skills. These are skills you should try to include on your resume.

Add industry skills like Scala and Python (Programming Language).

Add other common skills from your industry - such as Apache Kafka, Amazon Web Services (AWS) and Extract, Transform, Load (ETL) - into your resume if they're relevant.

Add skills into your work experience.

Incorporate skills - like Big Data Analytics, Docker Products and Hive - into your work experience too. This shows hiring managers that you have practical experience with these tools, techniques and skills.

Show your ability to analyze data.

In your Data Engineer resume, show evidence of where you worked with and analyzed data of all formats, whether they're surveys, spreadsheets or databases. We've highlighted examples in the infographic for reference.

Highlight data science skill sets.

Dealing with large data sets, cleaning them and uncovering business insights are important skill sets for a Data Engineer.

Use the exact job title.

Try to add the exact job title, Data Engineer, somewhere into your resume to get past resume screeners. See the infographic for how to do this.

Word Cloud for Data Engineer Skills & Keywords

The following word cloud highlights the most popular keywords that appear on Data Engineer job descriptions. The bigger the word, the more frequently it shows up on employer's job postings. If you have experience with these keywords, include them on your resume.

Top Data Engineer Skills and Keywords to Include On Your Resume

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Data Engineer Resume Templates

Here are examples of proven resumes in related jobs and industries, approved by experienced hiring managers. Use them as inspiration when you're writing your own resume. You can even download and edit the resume template in Google Docs.

Resume Example
Entry Level Data Analyst

Resume Example
Senior Data Analyst

Resume Example
Marketing Data Analyst

Resume Example
Financial Data Analyst

Resume Example
Senior Data Engineer

Resume Example
Big Data Engineer

Browse Skills from Similar Jobs

Frequently Asked Questions

What skills do hiring managers want to see on a Data Engineer resume?

On top Data Engineer resumes, skills like Apache Spark, Amazon Web Services (AWS), Data Engineering, Hadoop, Python (Programming Language), Scala, Extract, Transform, Load (ETL) and Apache Kafka appear most often.

Depending on the exact role you're applying to, skills like Big Data Analytics, Docker Products, Machine Learning, Big Data and Hive can also be effective keywords to include on your resume.

Target your Resume to a Job Description

While the keywords above are a good indication of what skills you need on your resume, you should try to find additional keywords that are specific to the job. To do this, use the free Targeted Resume tool. It analyzes the job you are applying to and finds the most important keywords you need on your resume.

It is personalized to your resume, and is the best way to ensure your resume will pass the automated resume filters.

Start targeting your resume

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