DATA PLATFORM ENGINEER SKILLS, EXPERIENCE, AND JOB REQUIREMENTS
Published: October 7, 2024 - 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