Freelancer Content Lead – AWS Certified Data Engineer Exam Prep Course

Freelancer Content Lead – AWS Certified Data Engineer Exam Prep Course Are you an experienced Data Engineer with a passion for AWS and creating exceptional learning experiences? Apply Here Who we are: neuefische GmbH, with our brands neuefische and Spiced Academy , has been Germany’s leading tech bootcamp provider for over ten years. Our programs create opportunities for people to launch fulfilling careers while driving the digital skills transformation across Germany. To date, over 7,000 participants have trained with us, and around 70% start working in tech immediately after the bootcamp. With 40% female participation , our courses not only build skilled professionals but also foster greater diversity in the tech industry. Many programs conclude with certifications from renowned partners such as IHK, Amazon, and CompTIA . Our vision: To transform lives by equipping people with the skills, confidence, and support they need to succeed in tech—online and on campus, in both German and English. Role Overview We are seeking a Subject Matter Expert (SME) with deep, hands-on experience in AWS data engineering. The SME will own the content of this 8-week exam-prep module — designing and creating learning outcomes, modules, hands-on labs, assessments, mock exams, and handouts and following pre established delivery methods and frameworks as the module belongs to a larger course. This person must be strategic, hands-on, and accountable for real impact to ensure the course content maps the vendor-neutral skills from our existing 14-week Data Engineering programme onto the AWS platform, closes every service-specific gap the certification requires, and prepares graduates for a next-generation professional course that equips learners to pass the AWS Certified Data Engineer – Associate (DEA-C01) exam while building real, production-grade AWS pipelines. The SME will be creating course content that goes well beyond exam cram — the content will enable learners to: Architect and implement AWS-native ingestion, transformation, and orchestration pipelines (Kinesis, MSK, DMS, Glue, EMR, Step Functions, MWAA) Design and tune AWS data stores for real access patterns (Redshift, DynamoDB, and specialty databases) Build and govern a cataloged, queryable data lake (Glue Data Catalog, Lake Formation, Athena, QuickSight) Operate pipelines securely and in compliance (CloudWatch/CloudTrail observability, IAM, KMS, Macie) The SME needs to create course content such that graduates can both build real AWS data engineering solutions in production and pass the AWS Certified Data Engineer – Associate (DEA-C01) exam — closing the gap between vendor-neutral data engineering knowledge and AWS-specific, certification-ready fluency. Format 8 weeks, full-time, one main topic per day (10 units/day) Audience Graduates of the neuefische 14-week Data Engineering programme Target outcome AWS Certified Data Engineer – Associate (DEA-C01) Core Tasks Evaluate our existing 14-week Data Engineering programme to identify the precise service-specific gaps the DEA-C01 exam requires, and validate the proposed 8-week weekly sequence (foundations → streaming and batch ingestion → transformation and orchestration → data store management → cataloging and analytics → operations, security, and governance → exam preparation). Define a compelling, exam-aligned curriculum outline weighted to the four DEA-C01 domains: Data Ingestion and Transformation (34%), Data Store Management (26%), Data Operations and Support (22%), and Data Security and Governance (18%). Develop advanced, practical content for this course – hands-on labs for every main topic (Kinesis, Firehose, MSK, Glue, EMR, Redshift, DynamoDB, Lake Formation, Athena, QuickSight, CloudWatch, KMS, and more), such that learners walk away with applied, production-ready AWS skills , not just exam trivia. Build high-impact assessments & practicals for this course – domain-aligned quizzes and knowledge checks modeled on the exam question style, service-comparison exercises (e.g., EMR vs. Glue, Redshift vs. Athena, Secrets Manager vs. Parameter Store), rubric-graded labs, peer review of pipeline and IaC configurations, and two full-length timed mock exams with detailed remediation plans. Build content to ensure industry relevance & exam currency, keeping materials aligned to evolving AWS services and the official DEA-C01 exam guide. Required Proven hands-on experience designing, building, and operating data engineering pipelines on AWS in production environments, spanning ingestion (Kinesis, MSK, DMS, AppFlow, EventBridge), transformation and orchestration (Glue, EMR, Step Functions, MWAA), and storage and analytics (Redshift, DynamoDB, Lake Formation, Athena, QuickSight) Strong practical experience with AWS security and governance services — IAM, KMS, Secrets Manager, CloudWatch, CloudTrail, and Macie — with demonstrated ability to operationalize these within real data engineering workflows Holds (or has held) the AWS Certified Data Engineer – Associate certification, or equivalent hands-on depth across all four exam domains, is highly preferred Prior experience in curriculum design, instructional design, course development, or professional training — ideally for technical, post-bootcamp audiences preparing for a vendor certification — is highly preferred This is a high-impact role shaping a flagship AWS certification module that complements an established 14-week Data Engineering curriculum; there will be close collaboration with product and teaching teams in a flexible, remote-friendly environment on course content, mock-exam design, and learner outcomes What we offer 🌱 👩‍🎓 An opportunity to join one of the fastest-growing companies in Tech-Education 🪴 A platform to grow as a part of a team of dedicated professionals 🎉 International, passionate (and fun) working environment * Even if you feel like ticking only 60% of the requirements, we would still like to review your application. At neuefische, we attach great importance to equal opportunities and respectful cooperation. All applicants should be valued equally - regardless of gender and gender identity, nationality, ethnic origin, religion or belief, disability, age, sexual orientation and identity. We value diversity and we are committed to integration and diversity. Department Product Locations Berlin, Hamburg Remote status Fully Remote