Intermediate Big Data Professional Program
Start at $499 and master enterprise big data architectures in 16-24 weeks. This professional program teaches you to design scalable data pipelines, optimize distributed systems, and lead analytics teams—with 1-on-1 mentorship from a 10-year industry veteran.
What You'll Learn
Career-ready skills, mapped to real hiring outcomes.
- Design and deploy distributed data pipelines using Apache Spark and Kafka
- Optimize SQL queries and tune database performance on large-scale datasets
- Build real-time analytics architectures with cloud platforms (AWS, GCP, Azure)
- Implement data governance frameworks and ensure compliance across data ecosystems
- Configure and monitor big data infrastructure using Docker, Kubernetes, and orchestration tools
- Extract actionable insights by applying statistical methods and machine learning to petabyte-scale data
Course Curriculum
5 modules · structured, self-paced.
Module 01 Distributed Systems & Data Architecture Foundations
- Hadoop ecosystem overview
- HDFS architecture and replication
- MapReduce programming model
- Cluster design best practices
Module 02 Apache Spark: Processing & Optimization
- Spark SQL and DataFrames
- RDD transformations and actions
- Query optimization and execution plans
- Partitioning and shuffle tuning
Module 03 Real-Time Data Streaming & Pipelines
- Apache Kafka architecture and producers
- Stream processing with Spark Streaming
- Event-driven pipeline design
- Latency and throughput trade-offs
Module 04 Cloud-Native Big Data & Data Warehousing
- Data warehousing on AWS Redshift and Snowflake
- Cloud storage optimization (S3, GCS, ADLS)
- Lakehouse architecture patterns
- Cost optimization and scaling strategies
Module 05 Advanced: Data Governance, MLOps & Capstone Project
- Data cataloging and metadata management
- Security, compliance, and access control
- ML pipeline orchestration and monitoring
- End-to-end capstone: design production-grade system
Who This Is For
Built for these professionals.
- 01 Data analysts and BI professionals ready to transition into big data engineering roles and own end-to-end pipeline development.
- 02 Software engineers seeking to specialize in data infrastructure and lead large-scale data architecture decisions.
- 03 Junior data engineers with 1-2 years experience who need structured mentorship to advance to mid-level or architect roles.
- 04 Technical product managers and analytics leaders who must understand data system design, scalability, and team management in enterprise settings.
Common questions about this program.
What programming languages and tools are required before starting?
You should be comfortable with Python or Java and understand SQL fundamentals. We assume you have worked with relational databases and basic ETL concepts. The course covers Scala for Spark, but we teach syntax quickly—the focus is on distributed systems thinking.
Does this program include cloud platform certifications?
Yes. The cloud module aligns with AWS Solutions Architect and Google Cloud Professional Data Engineer exam domains. We provide study guides and exam practice, though certifications are optional. Most graduates focus on portfolio projects instead, which carry more weight in hiring.
How does mentorship work, and what can James Okafor help me with?
You receive monthly 1-on-1 sessions with James to review your capstone architecture, discuss real-world design trade-offs, and navigate your transition to a data engineering role. He also reviews your resume and connects you with hiring managers in his network.
Can I complete this part-time while working full-time?
Yes. The program is designed for working professionals with 8-12 hours per week of study. The 16-24 week timeline gives flexibility—you can extend your pace. Most students complete modules at their own speed within a cohort calendar.
Get Started Today
Ready to start your
big data career?
Enroll now at $499 and get paired with James for your first mentorship call—limited cohort spots available.