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Open nowPosted 8 hours agoWe saw it 78 min after it went up

Data engineer

randstadhu312 open roles

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Your applicationOpen nowData engineerrandstadhu

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The clock on this job

Early applications get read.

13.9% of postings close within 7 days. Measured by our own scanner across the market. randstadhu postings stay open a median of 14 days.

Share of postings closed within
  1. 2.2%1 day
  2. 4.7%3 days
  3. 13.9%7 days
  4. 22.4%14 days
  5. 38.1%30 days
  6. 59.0%60 days
This job: posted 8 hours ago

randstadhu median: 14 days open

The posting

  • High Technical Impact: A unique professional challenge to shape the core data platform for a stable, market-leading global enterprise.
  • Competitive Compensation
  • Benefits Package: Cafeteria allowance and private health insurance package.
  • Flexibility: Hybrid working model requiring 2 days of office presence (Budapest) and offering 3 days of Home Office per week.

Required Qualifications

  • 3-7 years of professional data engineering experience
  • Strong proficiency in SQL; demonstrated ability to write and optimize complex queries
  • Hands-on experience with Databricks; working knowledge of Apache Spark fundamentals
  • Solid understanding of data warehouse and data lake concepts and architecture patterns
  • Experience designing and implementing ETL/ELT pipelines
  • Proficiency in at least one programming language (Python, Scala, or similar)
  • Experience with AWS (or another major cloud) - S3 / object storage, IAM, and secret management
  • Understanding of data quality, validation, and testing principles
  • Strong problem-solving skills and ability to work independently with guidance

Preferred Qualifications

  • Experience implementing medallion architecture patterns (bronze/silver/gold layers)
  • Familiarity with Delta Lake and its transactional capabilities
  • Experience preparing data for BI tools (Power BI, embedded analytics like Omni) or creating data models for analytics
  • Working knowledge of Delta Lake and Delta Live Tables (DLT) — declarative pipelines, expectations, incremental processing
  • Certification in Databricks for ‘Data Analyst’, ‘Data Engineer’, ‘ML Engineer’
  • Experience with version control (Git) and CI/CD best practices
  • Understanding of data governance, metadata management, and data cataloging
  • Exposure to streaming data and real-time pipeline requirements
  • Experience optimizing costs in cloud data platforms

Technical Skills

  • SQL (intermediate to advanced)
  • Databricks and Apache Spark
  • Python or Scala
  • Data pipeline design and implementation
  • Data quality and validation
  • Cloud platforms (AWS, Azure, or GCP)
  • BI design and dashboards
  • Relational and non-relational databases
  • Translate business questions into reliable data products — from requirements through delivery and iteration
  • Develop and optimize SQL queries, materialized views, and pre-aggregated summaries to keep dashboard latency and cost in check
  • Build ETL and ELT processes for ingesting, transforming, and validating data from multiple sources
  • Build and maintain gold and published-layer datasets for analytics and BI consumption
  • Partner with analytics and BI teams to prepare curated datasets for embedded analytics (e.g., Omni) and BI dashboards (e.g., Power BI)
  • Monitor data pipeline health, troubleshoot failures, and implement alerting and observability solutions
  • Ensure data quality, accuracy, and consistency across all pipeline stages
  • Participate in code reviews, documentation, and knowledge sharing with the team
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