Top 10 In‑Demand IT Skills for 2019 Every Engineer Should Master

1. DevOps

DevOps engineers have shown strong growth, with job postings increasing over 100% and average salaries around $123,000. Mastering automation and configuration‑management tools is essential:

Continuous integration/delivery: Jenkins Infrastructure as code: Puppet, Chef, Ansible, SaltStack Monitoring and alerting: Nagios Version control: Git Industry‑recognized DevOps certifications are recommended to validate these skills.

2. Big Data & Hadoop

Hadoop remains a cornerstone for large‑scale storage and parallel processing. Professionals should understand:

Hadoop architecture and ecosystem (HDFS, MapReduce)

How HDFS provides distributed file storage

MapReduce programming model for batch processing

Knowledge of complementary projects (e.g., YARN, Hive, Pig) is also valuable.

3. Python & Django

Python is the fastest‑growing language for 2019 and a common entry point for developers. Key points:

Python’s extensive standard library and third‑party ecosystem

Django framework follows the MVC (Model‑View‑Controller) pattern

Building web applications with Django includes routing, ORM, and template rendering

4. Data‑Science with R and Python

R and Python are the primary languages for data‑science workflows. Effective practice involves:

Working on real‑world projects and case studies

Using big‑data tools such as Hadoop and Spark for data ingestion and processing

Deploying models on cloud platforms (Microsoft Azure, Amazon AWS)

Core libraries include pandas, numpy, scikit‑learn (Python) and tidyverse, caret (R).

5. Machine Learning

Demand for ML engineers requires proficiency in:

Programming: Python, Spark (PySpark), R, SQL

Statistical foundations and feature engineering

TensorFlow (including the TensorFlow API certification)

Typical applications: facial recognition, speech recognition, text mining

6. Artificial Intelligence

AI specialists need a solid grounding in:

Machine‑learning algorithms and model evaluation

Parallel and distributed computing concepts

Data mining techniques and algorithm engineering

Strong computer‑science and mathematics backgrounds are assumed; senior AI roles can command salaries of $300k–$500k.

7. Robotic Process Automation (RPA) Tools

RPA is a key technology for digital transformation. Hands‑on experience with the following platforms is essential:

UiPath

Automation Anywhere

Blue Prism

8. AWS Certification

AWS holds roughly 40% of the global cloud market. Core services to master include:

Elastic Compute Cloud ( EC2)

Relational and NoSQL database services (RDS, DynamoDB)

Storage services (S3, EBS)

Fundamental IaaS and PaaS concepts

Certification programs help close skill gaps for cloud‑focused roles.

9. Tableau

Tableau is a leading business‑intelligence visualization tool. Important capabilities to learn:

Creating filters, calculated fields, and table calculations

Data blending from multiple sources

Designing interactive dashboards

10. Digital‑Marketing Analytics

Analytics for digital marketing focuses on extracting insights from customer data and measuring ROI. Core topics include:

Key performance indicators (KPIs) and measurement frameworks

Website optimization and A/B testing

Social‑media analysis

Google Analytics usage

Sentiment mining and text analysis