The Big Data Challenge – Knowing What You’re Hiring For

June 25th, 2019 by ifi-admin

Data science, data engineering and data analytics are broad, ambiguous terms that describe a long list of skills and job titles in the realm of data analytics.

“From the 30,000 foot view, a data scientist needs a mastery of the tools and techniques to access, transform, analyze and leverage the data collected by their organization,” said Kay Durkin, founder of Phoenix Partners.

“When hiring data scientists or analysts, it’s important to know the roles that these people will fill and their purpose.”

A good data strategy requires a number of qualified individuals dedicated to each stage of the process from collecting, to warehousing, to analyzing and to using that data to transform the business. This means building a team of people who can write algorithms, manage and collate data, interpret the data and communicate it to key stakeholders.

With the availability of technical talent at an all-time low, the market is exceptionally tight for finding skilled developers who possess specialized knowledge in Apache Hadoop; Apache Spark; NoSQL; Machine Learning and Data Mining; and Data Visualization.

The added dimension of possessing solid “soft skills” to communicate with business users can make the search even more daunting. It’s important to hire someone with strong communication skills to help balance the more technical side, especially since big data is an emerging trend in business. Not everyone in the company will understand the concepts of big data and their importance.

While technical skill assessment is essential in hiring big data team members, it’s also important to look for candidates who are innovators willing to push the boundaries in an emerging field.

Roles on a Big Data Team

Technologies in the big data field are role based. The following describes some of the key roles required to build a big data team.

1. Business Intelligence (BI) analyst

BI analysts need experience in database technology, analytics and reporting tools. Businesses typically look for candidates with a bachelor’s degree in computer science, information systems or engineering. Companies are looking for candidates with the skills to understand their unique data needs and then communicate those to business users. Ideal candidates may hold multiple degrees and show an interdisciplinary approach to problem-solving.
Certifications to look for: Certified Business Analysis Professional (CBAP®) or PMI Professional in Business Analysis (PBA).

2. Cloud architect/Data architect

Cloud architects oversee the company’s cloud computing strategy and are responsible for deploying, managing and supporting cloud applications. Cloud architects typically have a strong understanding of multiple operating systems in addition to networking, programming and security skills.

3. Cloud systems engineer/Data engineer

Cloud systems engineers are responsible for developing, planning, designing, installing, managing, maintaining and supporting IT cloud systems for data warehousing. These professionals typically work with Amazon Web Services, OpenStack, Microsoft Azure, and other popular cloud services.

4. Data scientist

While you need a BI analyst to help understand and communicate data patterns from a business perspective, a data scientist is the person who helps gather, process and analyze data. Look for candidates skilled in communicating those findings and offering recommendations to others in the business.

Data scientists are typically expected to be experts with skills such as R, SAS, Python, SQL, MatLab, Hive, Pig, and Spark. They should hold higher degrees in quantitative subjects such as statistics and mathematics and are proficient in big data technologies and analytical tools.

5. Database developer

Database developers are responsible for managing database architecture and developing new database servers. They’re tasked with developing database systems based on front-end-user requirements using SQL code. These IT professionals need strong problem-solving and troubleshooting skills as well as a long list of technical skills.

6. Data analyst

Data analysts are generalists. They play a variety of roles, from acquiring massive amounts of data to processing and summarizing it. Data analysts are expected to know R, Python, HTML, SQL, C++, and Javascript. They need to be very familiar with data retrieval and storing systems, data visualization and data warehousing using ETL tools, Hadoop-based analytics, and business intelligence concepts.

Are you looking to build a Big Data team? Talk to Phoenix Partners.


 
 
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