7 Key Skills You Need to Become a Data Engineer
The digital economy is thriving, and data has become the new currency. Be it making logistics within supply chains more efficient or personalizing user experiences in e-commerce, companies are increasingly reliant on real-time, actionable data. But raw data is of limited utility—it’s the work of data engineers that converts scattered information into structured insights.
Table Of Content
Data Engineering Is the Career of the Future
7 Essential Data Engineering Skills for a Thriving Career
How Jaro Helps
Ready to Future-Proof Your Career?
Frequently Asked Questions
Data Engineering Is the Career of the Future
*fynd.academy
As India’s digital base broadens and global players accelerate their cloud deployment and analytics initiatives, demand for data engineering skills has grown at an exponential rate. Data engineering recruitment for BFSI, healthcare, and IT services sectors has witnessed double-digit growth, says the latest report by NASSCOM. It is no longer the terrain of tech startups alone—industries that are ages old are also laying investments in establishing solid data teams to remain competitive.
Have you ever asked yourself who interprets the terabytes of data that are created each second—from your financial transactions online to the performance data behind your favorite apps? In a more and more data-centric world, people of all walks of life are starting to ask themselves: which data engineering skills do I need to prepare to be a part of this change?
7 Essential Data Engineering Skills for a Thriving Career
If you are searching for a high-impact, future-proof career that is dynamic at all times, data engineering skills might be the next thing in your sights. Whether you’re from a software development background and looking to make a career switch, a non-technical background, or simply want to reskill and stay in the game, data engineering is a great career opportunity. It’s not coding—it’s designing the data environments that power businesses today.
This blog will help you learn about the seven essential data engineer skills required to excel in the field and how you can get started through qualified programs facilitated via Jaro Education’s platform.
1. Programming Language Skills
Why it matters: Programming is an integral data engineering skill. It assists professionals in dealing with data, automating operations, and integrating systems efficiently.
Top Languages to Learn:
- Python: Applied to data manipulation, scripting, and ETL pipelines
- Java/Scala: Applied to big data technologies like Apache Spark
- SQL: Applied to querying and manipulating relational databases
Language | Use Case | Learning Curve |
Python | ETL, automation, analytics | Beginner-friendly |
Java | Batch processing, backend integration | Moderate |
SQL | Database operations | Essential and fundamental |
Industry Insight: According to the LinkedIn Workforce Report, SQL and Python are among the most in-demand skills required for data engineers globally.
2. Database Management and Data Warehousing
Why it matters: Data engineers design data storage and organization systems that are easy to utilize, enabling analysts and business decision-makers to access data.
Database Engineer Skills to Highlight:
- Relational databases (MySQL, PostgreSQL)
- NoSQL databases (MongoDB, Cassandra)
- Data warehousing solutions (Amazon Redshift, Google BigQuery, Snowflake)
Market Demand:
70% of businesses today possess hybrid data environments; thus, flexible database engineer skills are critical (NASSCOM Tech Report).
3. ETL (Extract, Transform, Load) Development
Why it matters: ETL processes are data engineering’s bread and butter. They transform raw data into something analyzable.
Popular Tools:
- Apache NiFi
- Talend
- Informatica
- Custom Python- or Scala-based ETL scripts
Skill Gap Highlight: Despite widespread need, there remains a data engineering skills gap in experts who know how to build scalable and automated ETL pipelines.
4. Big Data Frameworks
Why it is important: The booming amount of data is overwhelming traditional processing tools. Batch processing is not able to cope with it. Big data frameworks provide efficient massive data processing.
Key Technologies:
- Apache Hadoop (batch processing)
- Apache Spark (real-time and batch processing)
- Kafka (stream processing)
Framework | Strength | Industry Usage |
Hadoop | Storage + batch processing | Legacy + government projects |
Spark | In-memory speed + ML support | Widely used in finance, e-commerce |
Kafka | Real-time streaming | Logistics, IoT, fintech |
5. Cloud Platform Expertise
Why it is important: The majority of modern data engineering pipelines run on cloud platforms, which ensure scalability, security, and collaboration.
Top Cloud Providers:
- AWS (Amazon Web Services)
- Microsoft Azure
- Google Cloud Platform (GCP)
Relevant Skills:
- Setting up data lakes (AWS S3, GCP Cloud Storage)
- Implementing managed ETL services (AWS Glue, Azure Data Factory)
- Data security and governance in the cloud
Industry Trend: By 2025, over 85% of organizations will adopt a cloud-first strategy, with cloud literacy becoming an important differentiator.
6. Data Modeling and Schema Design
Why it matters: Inefficiently organized data can lead to inefficiencies and inaccuracies. Well-maintained data modeling ensures that systems are scalable and maintainable.
Core Concepts:
- Star and snowflake schemas
- Normalization and denormalization
- Entity-relationship diagrams (ERDs)
Application Across Roles:
- Assists BI analysts with faster queries
- Improves integration between data systems
7. Soft Skills: Communication and Problem-Solving
Why it matters: Data engineers often work cross-functionally with analysts, data scientists, and business leaders. Translating technical issues into something actionable is an essential data engineering skill.
Key Competencies:
- Problem-solving mindset
- Clear documentation practices
- Collaborative communication
Advancement Tip: As professionals move higher up the data engineering career ladder, leadership and project management skills become increasingly crucial.
*testgorilla.com
How Jaro Helps
Data engineering upskilling requires more than self-learning—you need structured learning, industry-oriented content, and access to thought leaders. That’s where Jaro Education comes in.
Universities & Courses:
Jaro collaborates with top colleges and universities to provide you courses that are a mix of academic rigor and relevance. Here are our top programs for data engineering skill advancement:
- PG Certificate Programme in Applied Data Science & AI — IIT Roorkee
- PG Certificate Programme in Cyber Security Management and Data Science — IIM Nagpur
- Advanced Data Science Certificate Program — Rotman School of Management (UofT) & Pravartak Technology Innovation Hub of IIT Madras
Program Highlights:
- Duration: 6 to 12 months (program specific)
- Format: 100% online with faculty interaction and campus immersions (details may vary; check website for detailed program plans).
- Key Skills Trained: Big data tools, Python, Spark, cloud data engineering, real-life case studies
- Best Suited For: Working professionals, career aspirants, software developers looking for a career shift
What Sets It Apart:
- Individualized guidance to match career goals with the best-suited program
- Business insights to create skill-based modules
- Jaro Connect, a networking hub with peers, alumni, and industry experts, accessible to them
Jaro is a service partner—operating directly in collaboration with the premier institutes to offer world-class programs to students. In the case of certification programs, the certificate or degree is issued by the respective institute.
Ready to Future-Proof Your Career?
The right program can change the course of your career. With the guidance of Jaro Education’s expert-led counseling, you’re not only signing up for a course—you’re investing in a calculated learning strategy. Demand for skilled data engineers is no passing fad—it’s a fundamental part of the backbone of the digital economy. For career professionals of this age, getting the right mix of technical competency and industry-accepted credentials can create a whole new world of possibilities and accelerated data engineering skills.
If you’re contemplating changing careers to become a data engineer, add these seven key data engineering skills to your study schedule. And don’t forget, with the right mentorship and platform, your study process can be every bit as much about strategy as the career you’re looking to get into.
Begin your journey—Jaro has got your back along the way.
Frequently Asked Questions
