Data Engineer (Databricks)

15.1k - 21k PLN15 120 - 21 000 PLN/ mies./ mies.B2BB2B (netto)

MidZdalnie·WarszawaFull-time·B2B

#465443·Dodano 5 dni temu·0

Źródło: nofluffjobs.com

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Tech Stack / Keywords

Python SQL ETL Azure Databricks Spark Docker CI/CD Kubernetes KafkaPower BIAirflowDagsterdbt

Podsumowanie oferty

As a Data Engineer, you will design and develop data platforms and data transformation pipelines for projects across aerospace, energy management and automotive. The work uses technologies including Databricks, Azure, Apache Spark, Python and SQL.

Wymagania

At least 3 years of commercial experience implementing, developing or maintaining Big Data systems.
Strong programming skills in Python, including clean code and OOP design.
Strong SQL skills, including performance tuning and query optimization, and experience with data warehousing solutions.
Experience designing and implementing data governance and data management processes.
Deep expertise in Big Data technologies, including Databricks, Spark, Airflow, Kafka and other data orchestration and transformation tools.
Experience implementing and deploying solutions in cloud environments, preferably Azure.
Knowledge of building and deploying Power BI reports and dashboards for data visualization.
Excellent understanding of dimensional data and data modeling techniques.
Consulting experience and ability to guide clients through architectural decisions, technology selection and best practices.
Ability to work independently and take ownership of project deliverables.
Master’s or Ph.D. in Computer Science, Data Science, Mathematics, Physics or a related field.

Obowiązki

Design and optimize scalable data processing pipelines for streaming and batch workloads using Databricks, Apache Airflow and Dagster.
Architect and implement end-to-end data platforms, ensuring high availability, performance and reliability.
Lead the development of CI/CD and MLOps processes to automate deployments, monitoring and model lifecycle management.
Develop and maintain applications for aggregating, processing and analyzing data from diverse sources.
Collaborate with Data Science teams on Machine Learning projects, including text and image analysis, feature engineering and predictive model deployment.
Design and manage data transformations using Databricks, DBT and Apache Airflow.
Translate business requirements into technical solutions while ensuring performance and data quality.
Ensure data security, compliance and governance best practices across data pipelines.

Benefity

Language classes and sponsored training or conferences, including access to training materials and certifications through partnerships with Databricks and Anthropic.
Team-building events and an integration budget.
Medical and sports packages, eye care, psychotherapy and coaching.
Full work equipment, including a laptop and other necessary devices.

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