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Data Engineering Lead

1 tydzień temu

Warszawa, Mazovia, Polska Nityo Infotech Pełny etat

Why Nityo Infotech?

Nityo Infotech is a dynamic and collaborative team that values expertise, creativity, and customer satisfaction. We offer a range of benefits, including competitive salary, comprehensive training programs, and opportunities for career growth and advancement.

About the Role

We are looking for a highly skilled professional with a strong background in cloud computing and big data engineering. Your primary responsibility will be to engineer reliable data pipelines for sourcing, processing, distributing, and storing data in different ways, using cloud (Azure) data platform infrastructure effectively.

Key Responsibilities

  • Transform data into valuable insights that inform business decisions, making use of our internal data platforms and applying appropriate analytical techniques.
  • Develop, train, and apply data engineering techniques to automate manual processes, and solve challenging business problems.
  • Ensure the quality, security, reliability, and compliance of our solutions by applying our digital principles and implementing both functional and non-functional requirements.
  • Build observability into our solutions, monitor production health, help to resolve incidents, and remediate the root cause of risks and issues.
  • Codify best practices, methodology and share knowledge with other engineers.
  • Shape the Data and Distribution architecture and technology stack within our new cloud-based datalake-house, being a hands-on contributor and senior lead in the big data and data lake space, capable of collaborating and influencing architectural and design principles across batch and real-time flows.

Requirements

  • Experience in building Data Processing pipelines using various ETL/ELT design patterns and methodologies to Azure data solution, building solutions using ADLSv2, Azure Data Factory, Databricks, Python, and PySpark.
  • Experience with at least one of the following technologies: Scala/Java or Python.
  • Deep understanding of the software development craft, with focus on cloud-based (Azure), event-driven solutions and architectures, with key focus on Apache Spark batch and streaming, Datalakehouses using medallion architecture. Knowledge of DataMesh principles is an added plus.
  • Ability to debug using tools like Ganglia UI, expertise in optimizing Spark Jobs.
  • The ability to work across structured, semi-structured, and unstructured data, extracting information and identifying linkages across disparate datasets.