data engineer resume samples

written byChief Editor, EPAM Anywhere

As Chief Editor, Darya works with our top technical and career experts at EPAM Anywhere to share their insights with our global audience. With 12+ years in digital communications, she’s happy to help job seekers make the best of remote work opportunities and build a fulfilling career in tech.

As Chief Editor, Darya works with our top technical and career experts at EPAM Anywhere to share their insights with our global audience. With 12+ years in digital communications, she’s happy to help job seekers make the best of remote work opportunities and build a fulfilling career in tech.

Data engineers are in high demand, and having the right data engineer resume can be crucial in landing a role. Data engineers play a critical role in managing, processing, and analyzing data, making them an invaluable asset to any organization. However, getting a job as a data engineer can be challenging, especially in highly competitive markets.

One way to increase your chances of landing a job is by having a well-written and impactful data engineer resume. This article will explore tips for creating a winning data engineer CV and provide some sample resumes to get you started.

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Data engineer CV tips to land your next job

A well-crafted data engineer CV is the first step toward impressing hiring managers and landing your next job. Here are some tips to help you create a standout resume:

data engineer resume checklist
  1. Keep it concise: Your resume should be three pages long at maximum. Recruiters spend an average of just six seconds scanning each resume, so keep it short and sweet.
  2. Focus on the keywords: Job postings often have keywords you must include in your resume. Today, many companies use automated applicant tracking systems to filter out resumes, so make sure you use the exact keywords as those used in the job description.
  3. Highlight your skills: Data engineering requires a unique set of both tech and soft skills, so be sure to highlight your expertise in SQL and NoSQL, Python, ETL, Java, Hadoop, Spark, data management, and other relevant skills in the skills section.
  4. Showcase your professional experience: Highlight your expertise in data processing, data warehousing, database management, and data modeling in the experience section. Be sure to provide specific examples of how you have used your skill set to achieve target metrics.
  5. Include certifications: Certifications in relevant areas such as computer science, data science and visualization, or cloud computing can help set your job application apart from other candidates.
  6. Tailor your resume to the job: Read the job description carefully and tailor your resume to highlight your experience and skills that match the requirements of the position.

How to write your data engineer resume summary

Your resume summary is the first thing recruiters will see, so it's essential to make it impactful. Here's how to write a compelling data engineer resume summary:

  • Start with a headline: Use a compelling statement or question that grabs the reader's attention. Your headline should describe your expertise in data engineering.
  • Outline your experience: Summarize your years of experience and expertise in data engineering and related technologies.
  • Provide quantifiable results: Detail the measurable results you achieved with your data engineering initiatives, such as improving data processing time or increasing data accuracy.

Data engineer resume summary samples

Here are a few examples of data engineer resume summaries to give you an idea of what to include in yours:

Data engineer resume professional summary #1

  • Software engineer with 8 years of experience.
  • Experienced in building data processing pipelines, from bespoke Python-based ones to those powered by cloud services.
  • Data analysis and modeling skills, from exploratory data analysis to building ML models on modern frameworks from the Python data science ecosystem.
  • Hands-on experience in solution architecture design, data modeling, prototyping, and software engineering (Microsoft .NET, Python, Azure, and Google Cloud platforms).
  • Proficient analytical, troubleshooting, and problem-solving skills.
  • Proactive and fast learner, constantly researching and evaluating cutting-edge technologies for production utilization.
  • Experience with all aspects of the software development lifecycle, from requirements management to production maintenance.

Data engineer resume professional summary #2

  • Skilled big data engineer: 10+ years of experience with big data/Hadoop and Cloud technologies – Spark, Hive, Flink, Presto, Snowflake, Map Reduce, Tez, HDFS, YARN, Amazon AWS
  • Skilled data warehouse developer with 13+ years of experience in IBM DB2, Oracle, Microsoft SQL Server, and Teradata
  • Strong hands-on experience running, monitoring, tuning, and optimizing ad-hoc SQL, batch ETL, and streaming workloads for large-scale analytics in cloud
  • Solid business intelligence solutions design skills
  • Strong knowledge of ETL design
  • Sufficient knowledge of full software application development lifecycle
  • Deep understanding of big data and Cloud technologies; used Hadoop tools in real project; training and mentoring other team members
  • Experienced Windows and Linux user with administration knowledge
  • Excellent communication skills
data engineer resume professional summary sample

Data engineer skills to list in your resume

Data engineering requires a unique set of skills that go beyond technical proficiency. Here are some essential skills to include in your data engineer resume:

  1. Technical skills: SQL, Python, ETL, Java, Hadoop, and Spark, to name just a few, are critical hard skills for data engineers. Ensure that you highlight your proficiency in these areas and any additional technical skills relevant to the job, which will be verified during your data engineer tech interview.
  2. Analytical skills: Data engineers need strong analytical skills to analyze complex data sets, identify patterns, and make data-driven decisions. Highlight your ability to use data to solve problems and improve business outcomes.
  3. Communication skills: Data engineers often work with cross-functional teams, including data scientists, business analysts, and executives. Highlight your ability to communicate complex technical concepts to non-technical stakeholders and collaborate effectively with others.
  4. Project management skills: Data engineering projects can be complex and involve multiple stakeholders. Highlight your experience in managing projects, including project planning, execution, and tracking.
  5. Data modeling skills: Data modeling is a critical skill for data engineers. Highlight your ability to design and implement data models that meet business requirements and improve data pipeline efficiency.
  6. Problem-solving skills: Highlight your experience diagnosing and troubleshooting data engineering issues. Demonstrate your ability to solve complex problems with creative solutions quickly and efficiently.

The same applies if you’re building your lead data engineer resume or even a data engineer manager resume.

sample data engineer skills for a resume

How to showcase your data engineer projects in a resume

As a data engineer, you’ve likely worked on a variety of projects that demonstrate your skills and experience. Here's how to showcase your data engineer projects in your resume:

  1. Choose your best projects: Select two or three projects that demonstrate your range of skills and experience. Make sure they are relevant to the job you are applying for.
  2. Provide project details: Provide details about each project, including the problem you were trying to solve, the data sources you used, and the tools and techniques you used to analyze and process the data.
  3. Highlight your achievements: Quantify the impact of each project by highlighting specific achievements, such as improving data processing time or increasing data accuracy.
  4. Use bullet points: Use bullet points to make your project details easy to read and scan. Make sure to use action verbs and be specific about your role in each project.
  5. Include a link to your portfolio: If you have an online portfolio or GitHub repository, include a link in your resume so recruiters can view your work.

To best describe your projects, take a look at our advice on software engineering portfolios or head straight to downloading our free project description templates.

How to describe your data engineer roles and responsibilities in a resume

When describing your roles and responsibilities as a data engineer, it's essential to focus on your accomplishments rather than your day-to-day tasks. Here's how to describe your data engineer roles and responsibilities in your resume:

  1. Provide an overview: Start by providing an overview of your role, including the type of organization you worked for and the size of the team you were on.
  2. Highlight your accomplishments: Use bullet points to highlight specific accomplishments, such as designing and implementing ETL pipelines or improving data processing efficiency.
  3. Use data: Whenever possible, use data to quantify your achievements. For example, you might say that you reduced data processing time by 30% or improved data accuracy by 20%.
  4. Be specific: Be specific about your role in each accomplishment. For example, if you led a project, make sure to highlight your leadership skills and the specific actions you took to achieve the project's goals.
  5. Tailor your descriptions: Tailor your descriptions to match the requirements of the job you are applying for. Focus on the skills and experience that are most relevant to the position.
data engineer roles and responsibilities: resume sample

Stand out with a cover letter

While your resume is essential, a well-crafted data engineer cover letter can help you stand out from other candidates. Here are some tips for creating a compelling data engineer cover letter:

  1. Customize your letter: Use the job description to tailor your letter to the requirements of the position. Highlight your experience and skills that match the job requirements.
  2. Highlight your achievements: Use specific examples to highlight your achievements and demonstrate your value to the organization.
  3. Be concise: Keep your letter to one page and focus on the most critical information. Recruiters receive many applications, so make sure your letter is easy to read and scan.
  4. Explain why you are a good fit: Explain why you are interested in the position and why you would be a good fit for the organization. Research the company and use this information to show that you are familiar with their goals and values.
  5. End with a call to action: End your letter by asking for a technical interview and providing your contact information. Make it easy for recruiters to contact you by including your email and phone number.

Senior data engineer resume sample

A senior data engineer resume needs to reflect your experience and leadership skills.


Senior Data Engineer


  • 9+ years of experience in the data processing field
  • Have worked in a variety of positions, including key developer, solution designer, and data architect
  • Strong engineering background combined with closely working with business customers, providing a broader understanding of business needs, objectives, and expectations of data projects
  • Development and implementation of ETL
  • Technical documentation preparation: detailed data workflow description, solution design and architecture, technical requirements specification
  • Ability to prioritize and make effective estimations
  • Perform code review
  • Direct communication with customers



  • SQL
  • Oracle RDBMS
  • Toad for Oracle
  • Apache Parquet
  • Apache Spark
  • Azure Blob Storage
  • Azure Data Factory
  • Azure Data Lake Storage
  • Azure Data Share
  • Azure Databricks
  • Azure Event Hubs
  • Azure Pipelines
  • Azure Repos
  • Azure SQL Database
  • Azure Stream Analytics
  • Azure Synapse Analytics
  • IBM Cognos Analytics
  • Microsoft Azure
  • Microsoft Power BI
  • PySpark
  • Python
  • UML

Engineering practices:

  • DWH & DB Concepts
  • Data Analytics Engineering
  • Data Preparation
  • Oracle SQL
  • Data Integration
  • Data Provisioning
  • Data Solution Architecture
  • Dataflow Orchestration & Monitoring
  • ETL/ELT Solutions
  • Oracle
  • Oracle PL/SQL

Leadership & management:

  • Agile
  • Kanban
  • Teamwork and сollaboration
  • Mentoring


June 2022 - present

Project Role: Senior Data Engineer

Customer Domain: Telecommunications

Team size: 15+ developers; 2 PMs, Solution Architect, DevOps


  • Rebuild of legacy on-premise Oracle-based data warehouse to a data lake based on Azure Cloud
  • Meet delivery and migration timelines to support smooth transition to a new operational system
  • Development and implementation of ETL pipelines according to the DWH design and architecture (Azure Synapse, ADLS Gen2, Databricks, Azure DevOps)
  • Business layer design
  • Create data models in SAP PowerDesigner
  • Technical documentation preparation: detailed data workflow description, solution design and architecture, technical requirements specification
  • Data profiling
  • Preparation and participation in POCs and demos

Database: Databricks, Oracle 12c, PostgreSQL

Tools: Azure Synapse, ADLS Gen2, Azure DevOps, SAP PowerDesigner, Toad for Oracle, DBeaver,, TortoiseSVN, JIRA, Confluence

Technologies: Azure ADLS Gen2, Delta Lake, Data Bricks, Azure Synapse Workspace, SQL


BA in Computer Technologies, 2014


English B2

Ukrainian Native

A data engineer resume example for experienced candidates

Experienced candidates should focus on specific achievements and highlight their technical expertise.


Lead Data Engineer


  • 10+ years of ETL development and data integration experience
  • A broad knowledge of DWH/BI disciplines: data warehousing, data integration, data processing, data modeling
  • Knowledge of SDLC
  • Advanced experience in a stack of RDBMS technologies and database performance tuning
  • Advanced experience with ETL tools: Informatica, IBM DataStage, and MPP solutions
  • 8+ years of experience in cross-platform solution delivery and network technologies
  • Excellent analytical/communication skills and effective teamwork


  • Batch data processing
  • Business intelligence methodologies: Dimension modeling, EDW, ODS
  • Distributed data processing: IBM DataStage, Hadoop M/R, Apache Spark
  • Cloud: AWS [Security / S3 / Redshift / Athena / Data Catalog / Glue]
  • OOP: Java Core [Streams, Collections, Multithreading]
  • Operating Systems: Unix/Linux/Windows
  • Version Control Systems: Svn, Git
  • CI/CD: Flyway, Bamboo, Ansible
  • Scripting and Procedural languages: PL/SQL, SQL, Shell Scripting


November 2019 - now

Project Role: Key data engineer

Customer Domain: Life Sciences & Healthcare

Team size: 7 developers, BA and QA engineers

Project description: Continuous enhancement and development of a solution that helps to reveal, manage, and reduce risks in third-party relationships by consolidating all procurement and sales information in one central repository built in AWS Cloud with Tableau analytics on top of it.


  • ETL process design and implementation: Apache Airflow/AWS Redshift/Python
  • Mentoring other developers: code review and knowledge sharing
  • Release planning and deployment activities
  • ETL maintenance and continuous improvement of the data delivery process
  • Elicitation and troubleshooting of data quality issues

Database: AWS Redshift [S3/Athena/Data Catalog]

Tools: AWS [S3/EC2/Lambda/Glue], GitLab, Ansible, Apache Airflow 1.15


MA in Information Systems, 2008


English C1

Big data engineer resume sample

If you are a big data engineer, your resume should emphasize your skills in managing and processing large volumes of data.


Lead Big Data Engineer


A certified full-stack Java developer with solid data background and 14+ years of experience in building enterprise applications, frontend, backend, and automation.

  • As a big data engineer, I developed ETL jobs using AWS to move multiple data sources into a data lake.
  • As a full-stack Java engineer, I developed the front end for web applications using Wicket, React and Redux, and REST web services.
  • Experienced in automation and functional testing using JUnit, Selenium, and WebdriverIO.
  • 10 years of experience working with agile methodologies.
  • Worked as technical lead for 10 years building teams from 3 to 7 people.
  • Worked as a reporting manager for 5 years coordinating 6 different teams with a total of 25 people.
  • Mentored my team members to improve their skills and expertise.


  • Amazon Elastic Container Service
  • Apache Airflow
  • Apache Kafka
  • Databricks
  • Spring
  • Java
  • Amazon EC2
  • Amazon S3
  • Apache Hive
  • Apache Maven
  • Apache OpenJPA
  • Apache Spark
  • Apache Struts


  • Databricks certified developer
  • Java 6 programmer
  • Java EE 5 business component developer
  • Database associate DB2 9 Fundamentals
  • Websphere MQ v7 administration


July 2018 - now

Project Role: Big data engineer

Customer Domain: Business Information and Media

Project description: Working on user activity ingestion in near real-time to calculate and provide user activities for personalization and post-processing projects.


  • Enhanced the REST API that receives the user activities to back up data if the Kafka server is down.
  • Created a POC to use KSQL to provide real-time feeds for a specific session in a Web Socket application that was later implemented in production.
  • Created an ETL batch process with Spark and Scala to calculate the time expended in videos and ads.
  • Created multiple Airflow dags to orchestrate various processes.
  • Created cloud formation scripts to deploy the infrastructure to run Docker containers in Fargate for REST APIs, using ALBs and autoscaling to deploy machine learning models running in Docker containers. I also created DAGs to trigger clusters and run ETL processes in EMR.
  • Migrated multiple project code and infrastructure to a different AWS account, migrated jobs from TeamCity to Jenkins, and migrated batch processes to use CloudFormation scripts.

Database: MySQL

Tools: Intellij, Docker, Airflow, AWS, Blazemeter, Qubole, Databricks, Cloudformation, Jenkins

Technologies: Spring, Kafka Streams, Java, Apache Spark, Scala


BA in Engineering & Computational Systems, 2013


English C1

Spanish Native



big data resume example


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Download a resume template for data engineers

Consider downloading a template if you need help crafting a data engineer resume. A resume template can ensure that your resume is well-organized and includes all the essential information needed to impress recruiters. Our template will ensure you have all the relevant information in your resume, such as job history, technical skills, and certifications.

Apply for a data engineer job at EPAM Anywhere

EPAM Anywhere offers a wide range of remote data engineering jobs. With EPAM Anywhere, you can build your work around your lifestyle and enjoy the stability of full-time employment along with the wealth of career development support resources we have to offer.

Alternatively, use our Find Me a Job service, and we will match you with suitable jobs in your area. Be sure to include all relevant information about your experience, skills, and certifications on your CV so recruiters know exactly what makes you stand out from other candidates!

written byChief Editor, EPAM Anywhere

As Chief Editor, Darya works with our top technical and career experts at EPAM Anywhere to share their insights with our global audience. With 12+ years in digital communications, she’s happy to help job seekers make the best of remote work opportunities and build a fulfilling career in tech.

As Chief Editor, Darya works with our top technical and career experts at EPAM Anywhere to share their insights with our global audience. With 12+ years in digital communications, she’s happy to help job seekers make the best of remote work opportunities and build a fulfilling career in tech.

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