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Lead Data Engineer

Skills

agileairflowautomationbigqueryci cdclouddata engineeringdata lakedata pipelinesdevopsgcpgithiveinfrastructure as codepysparkpythonscrumsqltest automationPythonGitCI/CDSQL

Description

zł115,200.00 – zł229,200.00 / year | 3-4+ Yrs Exp | Bachelor’s / Master’s in CS, Math, Physics, or Engineering | Lead Data Engineer | GCP Data Lake & Cloud Infrastructure | Wrocław, Poland | On-site / Hybrid | Full Time

Lead Data Lake Architecture, PySpark/Airflow Pipeline Engineering, and GCP Data Platform Initiatives for Viessmann Climate Solutions

Join Viessmann Technika Grzewcza (a Carrier company) as a Lead Data Engineer in Wrocław, Poland. Bringing 3 to 4+ years of data engineering experience with Data Lake architectures, SQL, and Python, this senior technical leadership role drives data pipeline design, code quality, and cloud data architecture. You will mentor data engineers, implement DevOps/CI/CD practices, and build scalable batch and streaming pipelines leveraging Google Cloud Platform (BigQuery, Dataflow, Dataform), PySpark, and Airflow.

Key Responsibilities:

  • Lead the technical design, development, and maintenance of scalable Data Lake solutions and enterprise data architectures.
  • Enforce high-standard coding practices, lead technical code reviews, and establish software engineering standards across the Data Engineering team.
  • Mentor junior and mid-level data engineers, guiding their technical development and problem-solving skills.
  • Partner closely with enterprise architects and business analysts to translate complex business requirements into technical backlogs and data models.
  • Implement automation practices, automated testing frameworks, CI/CD pipelines, and Infrastructure as Code (IaC) across cloud data environments.
  • Drive data pipeline optimizations, resolve complex technical blockers, and oversee relational/non-relational database integrations.

Tools/Technologies Used:

  • Languages & Data Processing: Python, Advanced SQL, PySpark, Apache Beam, Hive, HDFS, Distributed Data Processing
  • DevOps & Engineering Standards: CI/CD Pipelines, Infrastructure as Code (IaC), Git, Relational Databases, Automated Testing, Agile/Scrum Frameworks

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