Programs · Credentialing

    ADaSci Certified Data Engineer (ACDE)

    ADaSci Certified Data Engineer (ACDE) official credential badge
    Verifiable credential

    The ADaSci Certified Data Engineer program is a 30-hour self-paced online certification designed to build practical expertise in modern data engineering. It offers end-to-end training in designing scalable data pipelines, managing cloud infrastructure, and ensuring data quality and governance.

    4.5(0)
    4,140 enrolled
    30h
    60 questions

    About This Certification

    Get certified by ADaSci, the premier global professional body for AI and Data professionals, and showcase your data engineering skills on a global platform. Earn a credential that reflects both technical depth and practical expertise. Gain industry-ready Data Engineering skills through hands-on learning, real-world tools, and cloud-based systems. This professional certification validates your ability to build scalable data solutions and offers global recognition for your proficiency in the modern data engineering landscape.

    02 — OUTCOMES

    What you'll learn

    Qualify for in-demand roles such as Data Engineer, Analytics Engineer, Cloud Data Engineer, and Big Data Engineer across industries.
    Build job-ready skills in designing, deploying, and operating scalable data pipelines used in real-world enterprise environments.
    Strengthen career mobility by enabling transitions from data analyst, backend engineer, or cloud engineer roles into data engineering positions.
    Enhance earning potential by validating expertise in high-demand technologies such as Apache Spark, Kafka, Airflow, and cloud data platforms.
    Gain confidence in architecting end-to-end data platforms, improving technical credibility in interviews, design reviews, and production discussions.
    Position yourself for senior and leadership roles by developing strong foundations in data architecture, governance, and platform scalability.
    03 — CURRICULUM

    Program courses

    1 course

    05 — WHO IT'S FOR

    Who this is for

    Data Engineers (All Experience Levels)
    Analytics Engineers and BI Professionals
    Backend and Platform Engineers working with data pipelines
    Database Developers and SQL Professionals
    Cloud Engineers transitioning into data engineering roles
    Data Analysts aspiring to build scalable data pipelines
    Big Data and Distributed Systems Practitioners
    Technology Professionals involved in data platform modernization
    Solution Architects designing data-intensive systems
    Graduate Students and Early-Career Professionals pursuing careers in data engineering
    06 — WHY CERTIFY

    Why get certified.

    Gain comprehensive expertise in modern data engineering architectures, tools, and design patterns across batch, streaming, and cloud-native systems.
    Build strong hands-on capability through practical exposure to industry-standard technologies such as Spark, Kafka, Airflow, and cloud data platforms.
    Demonstrate validated proficiency in designing, building, and operating scalable, reliable, and high-performance data pipelines.
    Enhance career advancement opportunities by aligning skills with in-demand roles in data engineering, analytics engineering, and platform engineering.
    Develop enterprise-ready knowledge in data quality, governance, lineage, and compliance, essential for production-grade data systems.
    Strengthen architectural decision-making skills by mastering trade-offs across storage, processing, and orchestration technologies.
    07 — RECOGNITION

    Recognition

    This certification provides industry-relevant recognition by validating practical proficiency in modern data engineering tools, architectures, and cloud-native data platforms. It demonstrates the ability to design, build, and operate scalable batch and streaming data pipelines aligned with real-world enterprise standards.

    The certification is aligned with current industry practices used across technology, finance, healthcare, retail, and manufacturing sectors, enhancing credibility with employers seeking production-ready data engineering skills. It signals readiness to contribute to data platform modernization initiatives, analytics transformation, and large-scale data-driven decision systems.

    By emphasizing hands-on implementation, architectural decision-making, and governance best practices, the certification is recognized as a strong indicator of applied competence rather than theoretical knowledge, strengthening professional standing in hiring, project selection, and career advancement contexts.

    10 — ALSO CONSIDER

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