Senior Data Infrastructure Architect

6 godzin temu

Kraków, Polska N-iX Pełny etat
Key Responsibilities:
  • Lead and mentor data engineers, fostering a collaborative and high-performing team environment.
  • Drive technical excellence by enforcing best practices in data engineering and development.
  • Design and implement scalable data infrastructure, build, maintain, and optimize data pipelines for ingestion, transformation, and activation.
  • Create and execute solutions to handle diverse data sources and high volumes of information.
  • Develop and maintain efficient data models and schemas for a cloud-based data platform.
  • Ensure data integrity and accessibility by developing and maintaining pipelines.
  • Partner with the Solution Architect to translate high-level designs into actionable implementation plans, and collaborate with the Technical Product Owner to align data solutions with business needs.
  • Integrate data from diverse platforms, ensuring scalability, security, and accuracy.
  • Enable data readiness for downstream analytics, reporting, and segmentation.
Requirements:
  • Over 7 years of experience showcasing technical expertise and critical thinking in data engineering.
  • Hands-on experience with DBT and strong Python programming skills.
  • Proficiency in Snowflake and expertise in data modeling are essential.
  • Demonstrated experience in building consumer data lakes and developing consumer analytics capabilities is required.
  • In-depth understanding of privacy and security engineering within Snowflake, including concepts like RBAC, dynamic/tag-based data masking, row-level security/access policies, and secure views.
  • Ability to design, implement, and promote advanced solution patterns and standards for solving complex challenges.
  • Familiarity with multiple cloud platforms (Azure or GCP preferred, with a focus on Azure).
  • Practical experience with Big Data batch and streaming tools.
  • Competence in SQL, NoSQL, relational database design (SAP HANA experience is a bonus), and efficient methods for data retrieval and preparation at scale.
  • Proven ability to collect and process raw data at scale, including scripting, web scraping, API integration, and SQL querying.
  • Strategic thinker with strong business acumen.
  • Capable of managing and organizing multiple projects simultaneously.
  • Experience working in global environments and collaborating with virtual teams.
  • A Bachelor's or Master's degree in Data Science, Computer Science, Economics, or a related discipline.

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