DATA PLATFORM ENGINEER SKILLS, EXPERIENCE, AND JOB REQUIREMENTS
Updated: Mai 19, 2025 - The Data Platform Engineer develops scalable, and distributes production systems focused on personalization and recommendation technologies. This position demonstrates profound coding prowess and design acumen, alongside a track record of autonomous project ownership and solution-oriented global thinking for significant business impacts. This role possesses deep expertise in a variety of AWS Cloud Services and big data tools, complemented by capabilities in serverless data processing frameworks, deployment technologies, No-SQL databases, and UX development for enhancing data scientist workflows.
Essential Hard and Soft Skills for a Standout Data Platform Engineer Resume
- Data Architecture
- Cloud Computing
- SQL Programming
- ETL Development
- Data Warehousing
- Data Modeling
- Python
- Data Security
- Big Data Technologies
- Performance Tuning.
- Problem Solving
- Communication
- Team Collaboration
- Adaptability
- Time Management
- Critical Thinking
- Attention to Detail
- Project Management
- Leadership
- Stakeholder Engagement.
Summary of Data Platform Engineer Knowledge and Qualifications on Resume
1. BS in Computer Science with 5 years of Experience
- Demonstrate a range of experience with Data and Analytics technologies and concepts.
- Strong technical skills, with experience researching, implementing, and onboarding new technologies.
- Experience working with cloud technologies and solutions, with preferred depth in AWS services.
- Ability to successfully execute proof of concept projects and implement new technologies.
- Understanding of new technology and trends including database and analytics technologies, data science, AI and machine learning.
- Creative and innovative mindset with the ability to drive to outcomes.
- Understanding complex technology solutions and how they interrelate with other technologies and business drivers across the enterprise.
- Ability to work with ambiguity and organize requirements to identify options.
- Ability to build productive relationships and collaborate with partners and stakeholders.
- Ability to perform grasping tasks throughout the entire work day (examples: handwriting, grasping of equipment/machines, paper manipulation, sorting, folding, handling stacks of paper)
2. BS in Data Science with 2 years of Experience
- Experience working in building internal data platforms, or heavily using internal or third-party data platforms and tooling.
- Strong understanding of modern data processing paradigms and tooling, OLTP & OLAP database fundamentals.
- Strong proficiency in one or more programming languages frequently used in a modern data stack, such as Python, Scala, and/or SQL.
- Solid understanding of common data engineering and integration tasks (data ingestion & validation, clickstream data processing, data warehousing, et al).
- Experience with any of Airflow, Spark, Scala, Beam, Parquet
- Expertise in SQL for analytics/reporting/business intelligence, including basic comprehension of query execution plans, and query tuning/optimization for Google BigQuery, Amazon Redshift, Snowflake, or similar.
- Experience working with semi- or unstructured data in a data lake.
- Experience working in data engineering or a similar discipline at an online marketplace or similar consumer technology company.
- Coding skills in Python and/or Go
- Experience designing public APIs (in a language and/or REST)
- Experience and comfort building everything on top of AWS
- Experience with Linux, and Docker
3. BS in Data Science with 3 years of Experience
- Experience with the development and maintenance of build scripts and the use of Jenkins for build automation.
- Experience with Python development
- Ansible/Chef/Puppet or similar deployment scripting language
- Experience in unit test automation
- Experience in continuous integration/deployment and development techniques
- Exposure to Scrum/Agile delivery methodologies
- A solid grounding in Hadoop Big Data technologies such as HDFS, YARN, SQOOP, Hive, Impala and general cluster management (AWS)
- Experience with Cloud (AWS) application and infrastructure services such as VPC, EC2, S3, IAM
- Experience with SQL skills for data analysis covering both Oracle and MS SQL Server.
- Ability to use MS Excel / Word / Visio / Wiki for documentation of architecture/design/implementation.
- Familiarity with ETL concepts and solutions.
- Familiarity with scheduling and orchestration tools.
- Familiarity with data extraction from 3rd party APIs.
4. BA in Software Engineering with 5 years of experience
- Strong experience in building scalable distributed and production systems, specifically around personalization and recommendation systems.
- Exceptional coding and design skills
- Experience working autonomously and taking ownership of projects.
- Ability to think globally, devising and building solutions that meet many needs and prioritize business impact
- Strong cross-functional communication skills that help simplify and move complex problems forward with business partners
- Expertise in various AWS Cloud Services like AWS S3, SNS, SQS, EMR, CloudFormation, DynanmoDB, CodePipeline, Lambda, IAM, EC2 etc.
- Experience in developing Serverless Data processing Frameworks using AWS Step Functions, Fargate, S3, SQS Glue and Athena.
- Experience working with big data tools such as Hadoop, Spark, Spark-SQL, Spark-Streaming, Kafka, Hive, Impala, Sqoop, Map-Reduce, etc.
- Knowledge of Deployment tools and technologies like Terraform, Ansible, Docker, Puppet and Jenkins
- Experience in No-SQL databases like Casandra and Mongo-DB
- Some UX development exposure and understanding the spectrum of personal workflows of data scientists
- Experience writing technical documentation and teaching people how to use the tools
Editorial Process and Content Quality
This content is developed by the Lamwork Editorial Team using structured analysis of real-world job data, skill requirements, and hiring patterns.
Research framework by Lam Nguyen, Founder & Editorial Lead.
Reviewed by Thanh Huyen, Managing Editor.
Learn more about our editorial standards.