Data analytics is the lifeblood of any successful business. Getting the technology right can be challenging but building the right team with the right skills to undertake data initiatives can be even harder.
Successfully deploying big data initiatives requires more than data scientists and data analysts. It requires data architects who design the “blueprint” for your enterprise data management framework, and it requires data engineers who can build that framework and the data pipelines to bring in, process, and create business value out of data.
Data architect roles and responsibilities
Data architects are senior visionaries who translate business requirements into technology requirements and define data standards and principles. They typically have years of experience in data design, data management, and data storage.
Typical data architect responsibilities include:
Translating business requirements into technical specifications, including data streams, integrations, transformations, databases, and data warehouses
Defining the data architecture framework, standards, and principles, including modeling, metadata, security, reference data such as product codes and client categories, and master data such as clients, vendors, materials, and employees
Defining reference architecture, which is a pattern others can follow to create and improve data systems
Defining data flows, i.e., which parts of the organization generate data, which require data to function, how data flows are managed, and how data changes in transition
Collaborating and coordinating with multiple departments, stakeholders, partners, and external vendors
Data engineer roles and responsibilities
Data engineers are responsible for managing and organizing data, while also keeping an eye out for trends or inconsistencies that will impact business goals. Data engineers design, build, and optimize systems for data collection, storage, access, and analytics at scale. They create data pipelines used by data scientists, data-centric applications, and other data consumers. Data engineers are typically skilled in technologies such as Hadoop, Spark, and other tools from the open source big data ecosystem, and at programming in Java, Scala, or Python.
Typical data engineer responsibilities include:
Developing, constructing, testing, and maintaining architectures
Data acquisition
Developing data set processes
Identifying ways to improve data reliability, efficiency, and quality
Deploying sophisticated analytics programs, machine learning, and statistical methods
Preparing data for predictive and prescriptive modeling
Using data to discover tasks that can be automated
Benefits of certification
If you’re looking for a way to get an edge for either of these essential data roles, certification is a great option. Certifications measure your knowledge and skills against industry- and vendor-specific benchmarks to prove to employers that you have the right skillset for the job.
Below is our guide to the most sought-after data engineer and data architect certifications to help you decide which cert is right for you. Not finding what you’re looking for, check out our list of big data and data analytics certifications.
If you would like to submit a big data certification to this directory, please email us.
The top 8 data engineer and data architect certifications
Amazon Web Services (AWS) Certified Data Analytics – Specialty
Cloudera Data Platform Generalist Certification
Data Science Council of America (DASCA) Associate Big Data Engineer
Data Science Council of America (DASCA) Senior Big Data Engineer
Google Professional Data Engineer
IBM Certified Solution Architect – Cloud Pak for Data v4.x
IBM Certified Solution Architect – Data Warehouse V1
SAS Certified Data Integration Developer
Amazon Web Services (AWS) Certified Data Analytics – Specialty
The AWS Certified Data Analytics – Specialty certification validates technical skills and experience in AWS data lakes and analytics services. It is intended to validate a candidate’s ability to define AWS data analytics services and understand how they integrate with one another. It also requires a candidate to know how AWS data analytics services fit in the data life cycle of collection, storage, processing, and visualization. Formerly known as AWS Certified Big Data – Specialty, this certification is active for three years from the date earned.
Organization: Amazon Web Services
Price: $300 registration fee for exam
How to prepare: Candidates should have at least five years of experience with data analytics technologies and at least two years of hands-on experience working with AWS. AWS offers an exam guide and the AWS Data Analytics Learning Path.
Cloudera Data Platform Generalist Certification
Cloudera has discontinued its CCP and CCA certifications in favor of the new Cloudera Data Platform (CDP) Generalist Certification, which verifies proficiency with the platform. The new exam tests general knowledge of the platform and applies to multiple roles, including administrator, developer, data analyst, data engineer, data scientist, and system architect. The exam consists of 60 questions and the candidate has 90 minutes to complete it. Other specialized certifications include CDP Administrator – Private Cloud Base, CDP Data Developer, CDP Data Analyst, and CDP Administrator – Public Cloud.
Organization: Cloudera
Price: $330
How to prepare: Cloudera recommends candidates take the Cloudera Data Analyst Training course, which has the same objectives as the exam.
Data Science Council of America (DASCA) Associate Big Data Engineer
The vendor-neutral DASCA Associate Big Data Engineer certification demonstrates knowledge of popular big data platforms, including Hadoop and Spark, and knowledge of proprietary and open source developer tools (including HBase, Hive, Pig, and HiveQL). It requires passing a 75-question online exam. There are three candidacy tracks that vary based on level of education and work experience.
Organization: Data Science Council of America
Price: $585 for the exam, standard exam preparation resources, shipping, digital badging, and credential kit
How to prepare: Registration for the program includes a full DASCA Certification Preparation Kit.
Data Science Council of America (DASCA) Senior Big Data Engineer
DASCA’s Senior Big Data Engineer certification is a step up from the associate credential, intended for experienced professionals. It requires passing an 85-question online exam. There are four candidacy tracks that vary based on level of education and work experience.
Organization: Data Science Council of America
Price: $650 for the exam, standard exam preparation resources, shipping, digital badging, and credential kit
How to prepare: Registration for the program includes a full DASCA Certification Preparation Kit.
Google Professional Data Engineer
The Google Professional Data Engineer credential certifies the ability to design, build, operationalize, secure, and monitor data processing systems. It requires passing a two-hour, multiple-choice and multiple-select certification exam. The exam has no prerequisites, though Google recommends candidates have three or more years of industry experience, including one or more years designing and managing solutions using Google Cloud Platform. The exam is available in English and Japanese and may be taken as an online-proctored exam from a remote location or as an onsite-proctored exam at a testing center.
Organization: Google
Price: $200 registration fee
How to prepare: Google offers an exam guide and on-demand or instructor-led training.
IBM Certified Solution Architect – Cloud Pak for Data v4.x
The IBM Certified Solution Architect – Cloud Pak for Data v4.x certification validates an individual’s ability to design, plan, and architect a data and AI solution in a hybrid cloud environment. A certified architect can lead and guide the implementation and operationalization of a solution that may include data governance, analytics, data science, machine learning, and AI. It requires passing a test that consists of six sections containing a total of 63 multiple-choice questions.
Organization: IBM Professional Certification Program
Price: $200
How to prepare: IBM offers a sample test and study guide. It also offers an assessment exam through Pearson VUE. There is also a learning path that takes about 13.5 hours to complete.
IBM Certified Solution Architect – Data Warehouse V1
The IBM Certified Solution Architect – Data Warehouse V1 certification validates an individual’s ability to design, plan, and architect a data warehouse solution. It requires working knowledge of data governance, data processing approaches, data stores and data virtualization, real-time processing solutions, and more. It requires passing a test that consists of seven sections containing a total of 62 multiple-choice questions.
Organization: IBM Professional Certification Program
Price: $200
How to prepare: IBM offers an assessment exam through Pearson VUE. In addition, IBM suggests courses on data topology, data warehousing, and data privacy.
SAS Certified Data Integration Developer
The SAS Certified Data Integration Developer certification program is for individuals seeking to validate their data integration development skills in the SAS 9 environment. The program focuses on defining architecture of the platform for SAS Business Analytics, creating metadata for source and target data, working with transformations, and more. The program requires passing a certification exam administered by SAS and Pearson Vue.
Organization: SAS Global Certification Program
Price: $180
How to prepare: SAS offers an exam guide, The SAS Data Integration Studio: Fast Track course, sample questions, and practice exams.
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