ITDS

Senior Cybersecurity Data Engineer – Azure

~18.7k - 22.5k PLN18 700 - 22 500 PLN/ mies./ mies.B2BB2B (netto)

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SeniorHybryda·KrakówFull-time·B2B·Umowa o pracę

#471264·Dodano 14 dni temu·0

Źródło: ITDS

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Tech Stack / Keywords

Azure Data FactoryAzure Databricks Azure Functions Azure Logic AppsAzure DevOpsPython Spark SQLKusto Query LanguagePower BI

Podsumowanie oferty

As a Senior Cybersecurity Data Engineer, you will support the Cybersecurity Risk Quantification team in developing and managing a mathematical model that measures how improvements to controls reduce risk exposure. You will build and maintain data pipelines and related data flows, working with technologies including Azure Data Factory and Azure Databricks.

Wymagania

At least 5 years of experience in data engineering.
Experience deploying complex cloud data and big data systems.
Experience applying data engineering methods within the cybersecurity domain.
Proven ability to design, build, and maintain data pipelines and ETL workflows across disparate datasets.
Experience with Azure Data Factory, Azure Databricks, Azure Functions, Azure Logic Apps, Azure Monitor, Azure Log Analytics, Azure Data Lake Store, S3, Synapse Analytics, and/or Power BI.
Practical knowledge of Azure DevOps, Bash or PowerShell, Azure CLI, Python, Spark, SQL, Kusto Query Language, Git, and CI/CD systems.
Advanced understanding of data transport, data pipelining, data cleansing, and data quality methods.
Experience analyzing incoming datasets, understanding schemas, and deriving schemas for data without existing structures.
Understanding of model lifecycle controls and experience working within data governance frameworks in a regulated environment.
Ability to communicate complex technical issues clearly and effectively to diverse audiences.
Fluent English.

Nice to have:

Experience with PMP or PRINCE2 methodologies.
Knowledge of Scrum or Kanban program management methods.

Obowiązki

Design, implement, improve, and support data flows and data-related technologies for analytics initiatives.
Build and maintain data pipelines and data buses that collect information from disparate internal and external sources.
Transport and deliver data to data warehouses and data lakes in the required format.
Apply advanced data manipulation techniques to ensure data availability and usability throughout data flows.
Ensure data quality, security, and compliance in line with regulatory and system requirements.
Provide ongoing technical support to stakeholders within and outside the science and analytics environment.
Implement data governance controls, including lineage, metadata, data quality rules, access controls, and retention policies.

Inne informacje

Only candidates with an existing legal right to work in Europe will be considered.

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