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Senior Data Engineer (Architecture & AI Foundations)
Отличная вакансия для опытного инженера: работа с передовым стеком (AI, Cloud), гибридный формат и фокус на архитектуру. Компания Appnovation известна своей культурой и интересными глобальными проектами.
Сложность вакансии
Высокая сложность обусловлена требованием опыта более 7 лет, необходимостью совмещать роли архитектора и разработчика, а также знанием современных AI-технологий (RAG, векторные БД).
Анализ зарплаты
Зарплата в объявлении не указана, но для Senior Data Engineer в Ванкувере рыночный диапазон составляет 130,000–170,000 CAD в год. Предложение Appnovation, вероятно, находится в этих пределах, учитывая высокие требования к архитектурному опыту.
Сопроводительное письмо
I am writing to express my strong interest in the Senior Data Engineer position at Appnovation. With over 7 years of experience in data engineering and architecture, I have developed a deep expertise in building robust ETL/ELT pipelines and designing scalable data models that serve as the backbone for advanced analytics and AI initiatives. My background includes extensive work with cloud platforms like AWS and GCP, as well as hands-on experience with modern tools such as dbt, Airflow, and Snowflake.
What excites me most about this role is the opportunity to bridge the gap between architectural design and hands-on implementation, particularly in the context of AI foundations. I have a keen interest in RAG architectures and vector databases, and I am eager to apply my skills in data governance and quality to ensure that AI/ML models are built on trustworthy data. I am confident that my technical leadership and collaborative approach will allow me to contribute effectively to Appnovation’s mission of delivering impactful digital solutions.
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Присоединяйтесь к Appnovation, чтобы проектировать фундамент для AI-решений будущего и трансформировать данные в реальную ценность!
Описание вакансии
About us
Appnovation is a global, full-service digital partner that combines Strategy, Experience & Design, Engineering and Managed Services. We build digital solutions that deliver real impact today and serve as foundations for future growth. Bold ambition. Practical action. Endless possibilities.
Appnovation is seeking a Senior Data Engineer who combines architectural thinking with hands-on delivery. We’re looking for someone who can design robust data architectures and build the pipelines that bring them to life.
In this role, you’ll help organizations transform fragmented data landscapes into unified, reliable platforms. You’ll work with modern cloud data technologies, contribute to the data foundations that support AI/ML initiatives, and play a key role in shaping how data is modeled, moved, and trusted across systems.
This is a hands-on role with architectural ownership — ideal for someone who enjoys both designing data systems and implementing them in practice.
Who you are
- You think architecturally about data, looking beyond individual pipelines to the broader ecosystem of how data flows, transforms, and creates value
- You’re equally comfortable whiteboarding data models and writing code to implement them
- You’re curious about how AI and ML are influencing data engineering, including areas like RAG architectures and vector databases
- You care deeply about data quality, governance, and lineage, and understand why trustworthy data is foundational
- You communicate effectively with both technical teams and business stakeholders, translating data capabilities into meaningful outcomes
- You approach legacy system consolidation as a problem to solve, not a burden, and enjoy bringing structure to complexity
- You stay current with the evolving data ecosystem and enjoy evaluating new tools and approaches
What you bring
A strong mix of the following will set you up for success in this role:
- 7+ years of experience in data engineering and/or data architecture roles
- Strong experience with at least one cloud data warehouse
- Experience designing data pipelines across batch, streaming, or event-based architectures
- Data modeling expertise, including dimensional modeling and conceptual, logical, and physical model design
- Strong SQL skills, including window functions, CTEs, query optimization, and performance tuning
- Proficiency in Python for data engineering tasks
- ETL/ELT pipeline development experience using modern tools (e.g. dbt, Airflow, or similar)
- Cloud platform experience (GCP and AWS), including cloud storage and data lake services
- Familiarity with event streaming platforms (Kafka, Pub/Sub, or similar)
- Practical understanding of data governance, quality, and lineage practices
- Experience with or interest in AI-assisted development tools
- CI/CD experience for data pipelines, including testing strategies for data transformations
- Experience working with Docker and containerized environments
Nice to have
Experience in one or more of the following areas is a plus, but not required:
- RAG (Retrieval-Augmented Generation) architectures or AI/ML data infrastructure
- Vector databases (Pinecone, Weaviate, pgvector, or similar)
- Agentic AI implementations
- Lakehouse architectures (Delta Lake, Apache Iceberg, or similar)
- Health or regulated data environments (HIPAA, GDPR)
- MLOps practices and ML pipeline development
- Real-time data processing and streaming analytics
- Legacy database migrations (e.g. MSSQL, MySQL consolidation)
- BI tools (Power BI, Looker, or similar)
- Workflow orchestration and automation tools (Airflow, Prefect, n8n, or similar)
- Infrastructure as Code tools (Terraform, Pulumi, or similar)
Why Appnovation
At Appnovation, you’ll work with collaborative, experienced teams on a wide range of client challenges. We value thoughtful technical leadership, clear communication, and continuous learning. Our environment is professional but human, with room to grow, experiment, and build meaningful solutions.
We offer:
- Flexible working arrangements (hybrid remote/in-office)
- Health benefits and wellness support
- Fitness allowance
- Opportunities to work across industries and modern data platforms
- A culture that values inclusion, collaboration, and professional growth
Appnovation is committed to fostering a diverse and inclusive workplace. We encourage applications from all qualified candidates, even if you don’t meet every requirement listed.
Thank you for your interest in a career with Appnovation Technologies! Please note that only those selected for an interview will be contacted.
At Appnovation, we recognize that diverse teams are the strongest teams. Diversity, Equity & Inclusion is not only something that we embrace - we celebrate it! We are proud to be an Equal Opportunity Employer and we encourage applicants from all backgrounds, lived experiences and industries to apply. Come join us at Appnovation, and learn more about how we stay true to our company values as we build better lives through better digital. Accommodations are available upon request throughout the recruitment process.
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Навыки
- SQL
- Python
- dbt
- Airflow
- AWS
- GCP
- Kafka
- Docker
- Terraform
- Data Modeling
- ETL
- ELT
- CI/CD
- Vector Databases
- RAG
- Snowflake
Возможные вопросы на собеседовании
Вакансия предполагает работу с AI-фундаментом. Важно понимать, как кандидат готовит данные для этих целей.
Как бы вы спроектировали архитектуру данных для системы RAG (Retrieval-Augmented Generation), учитывая необходимость обновления данных в реальном времени?
Роль требует навыков архитектурного проектирования.
Опишите ваш подход к выбору между Kimball (dimensional modeling) и Data Vault при проектировании корпоративного хранилища данных.
Упоминается работа с разрозненными ландшафтами данных.
Расскажите о вашем опыте консолидации легаси-систем: с какими основными трудностями вы сталкивались при обеспечении качества данных?
В стеке указаны dbt и Airflow.
Как вы организуете CI/CD и тестирование для dbt-проектов, чтобы гарантировать целостность данных в продакшене?
Вакансия требует владения Python для Data Engineering.
В каких случаях вы предпочтете использовать Spark/PySpark вместо чистого Python или SQL для обработки данных, и наоборот?
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