Introduction

In the digital age, the effective collection, transformation, and management of research data is essential for meaningful scientific discovery and innovation. Data Engineering for Research Data Pipelines Training Course equips learners with hands-on, cutting-edge skills in designing scalable, reproducible, and optimized data pipelines using modern data engineering tools and practices. This course is tailored for professionals who need to manage structured and unstructured research data efficiently—from raw ingestion to usable datasets ready for analysis and machine learning.

With data volumes growing exponentially, researchers and engineers need robust knowledge of technologies like Apache Airflow, Apache Spark, SQL, ETL/ELT frameworks, and cloud-based data solutions. This course bridges the gap between research data demands and practical data engineering skills by providing real-world scenarios and case studies in scientific research, healthcare analytics, social science, and environmental data.

Programme Curriculum

Data Engineering for Research Data Pipelines Training Course

Introduction

Course Objectives

Understand the fundamentals of data engineering in research environments.
Develop automated data pipelines for various research datasets.
Implement ETL and ELT strategies for structured and unstructured data.
Use Apache Airflow to schedule and monitor research data workflows.
Leverage Apache Spark for big data processing in research contexts.
Apply SQL and NoSQL for effective data storage and retrieval.
Design data lakes and warehouses tailored for academic and institutional research.
Ensure data quality, validation, and lineage in research projects.
Integrate cloud platforms like AWS, Azure, or GCP for research data infrastructure.
Analyze real-time and batch data for scientific studies.
Explore metadata management and documentation best practices.
Secure data governance and compliance in research pipelines.
Build scalable and reproducible data workflows for collaborative research.

Target Audiences

Data engineers in research institutions
University researchers and graduate students
Health informatics professionals
Government and NGO data analysts
Data scientists managing research data
IT professionals supporting research projects
Environmental and social science researchers
Research software engineers

Course Duration: 5 days

Course Modules

Module 1: Introduction to Research Data Engineering

Overview of data engineering in research
Role of data pipelines in scientific workflows
Research data lifecycle
Tools and technologies overview
Data formats in academia (CSV, JSON, XML, etc.)
Case Study: Research pipeline in clinical trial data management

Module 2: Data Ingestion and Collection

Batch vs. real-time ingestion
APIs and web scraping for research data
IoT and sensor data collection
Using Python and R for data extraction
Connecting to research databases
Case Study: Environmental data ingestion using IoT sensors

Module 3: ETL and ELT Design for Research

ETL vs. ELT in research environments
Data transformation techniques
Data validation and cleaning
Workflow optimization strategies
Open-source tools: Apache NiFi, Talend
Case Study: ETL process for national census datasets

Module 4: Workflow Orchestration with Apache Airflow

DAGs and task dependencies
Scheduling and triggering workflows
Monitoring and logging
Versioning research workflows
Integrating Airflow with cloud platforms
Case Study: Airflow-based pipeline for genomics research

Module 5: Big Data Processing with Apache Spark

Spark architecture and RDDs
Spark SQL for research queries
DataFrames and MLlib
Spark on Databricks or EMR
Optimizing research workloads
Case Study: Large-scale social media sentiment analysis

Module 6: Storage Solutions and Data Modeling

Relational vs. non-relational models
Schema design for research data
Cloud storage: S3, Azure Blob
Data lakes vs. warehouses
File formats: Parquet, Avro
Case Study: Storage design for medical imaging data

Module 7: Data Governance and Compliance

Data privacy in academic research
HIPAA, GDPR, and institutional compliance
Data lineage and auditing
Role-based access and IAM
Metadata and data dictionaries
Case Study: Compliance in university-hosted research projects

Module 8: Final Project and Capstone

End-to-end pipeline design
Selecting research data use case
Implementing ingestion, transformation, storage
Workflow orchestration and optimization
Presentation and peer review
Case Study: Capstone on public health research pipeline

Training Methodology

Instructor-led virtual or onsite sessions
Hands-on labs with real datasets
Guided projects with mentor support
Group discussions and peer review
Quizzes and knowledge checks
Final capstone project with feedback

Register as a group from 3 participants for a Discount

Send us an email: info@fineskilltrainingcenter.org or call +254769199797

Certification

Upon successful completion of this training, participants will be issued with a globally- recognized certificate.

Tailor-Made Course

We also offer tailor-made courses based on your needs.

Key Notes

a. The participant must be conversant with English.

b. Upon completion of training the participant will be issued with an Authorized Training Certificate

c. Course duration is flexible and the contents can be modified to fit any number of days.

d. The course fee includes facilitation training materials, 2 coffee breaks, buffet lunch and A Certificate upon successful completion of Training.

e. One-year post-training support Consultation and Coaching provided after the course.

f. Payment should be done at least a week before commence of the training, to Fineskill Training Center account, as indicated in the invoice so as to enable us prepare better for you.

Skills & Software Covered

Data pipelines ETL research data workflows

Programme Fee

Duration: 5 Days

Method: Online or Physical

Online Price: $1,000

Physical Price: $1,500

Certification: Accredited Certificate

View Available Dates 📄 Download Course Outline (PDF)

Available Sessions

Location

Month

Year

Sep 21 2026

21 Sep — 25 Sep 2026

💻 Online / Virtual session

Online $1,000