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Senior Data Engineer (Databricks)

21k - 28.6k PLN21 000 - 28 560 PLN/ mies./ mies.B2BB2B (netto)

SeniorZdalnie·WarszawaFull-time·B2B

#465447·Dodano 12 dni temu·0

Źródło: nofluffjobs.com

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Tech Stack / Keywords

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

Podsumowanie oferty

As a Senior Data Engineer, you will work with a team of technology experts on data engineering projects, including a data platform for aerospace companies, a platform transformation for an energy management association, and data pipelines for a global car manufacturer. You will design and develop scalable data platforms and pipelines using Databricks, Azure, Apache Spark, Airflow, and Dagster.

Wymagania

At least 5 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, 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, Kafka, DBT, Airflow, Dagster, 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.
Lead the development of CI/CD and MLOps processes for deployments, monitoring, and model lifecycle management.
Develop and maintain applications that aggregate, process, and analyze 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 practices across data pipelines.
Design the architecture and processes for a universal data platform for global aerospace companies, with technology selection at an early stage.
Implement a data catalog and secure integration solutions, and improve data quality monitoring for an energy management association’s data platform.
Build a data processing system for real-time streaming and batch data for a global car manufacturer, including data cleaning, normalization, and data model optimization.

Benefity

Language classes.
Sponsored training and conferences, including training materials and certifications through partnerships with Databricks and Anthropic.
Team-building events and an integration budget.
Medical and sports packages, eye care, and well-being support services, including psychotherapy and coaching.
Full work equipment, including a laptop and other necessary devices.
Referral bonus.
MyBenefit cafeteria.
Paid leave.
Training budget and in-house training.
Flexible working hours.
Free coffee.

Kursy językowe

Budżet konferencyjny

Dofinansowanie szkoleń

Szkolenia wewnętrzne

Spotkania integracyjne

Opieka zdrowotna

Karta sportowa

Premie

Dodatkowe benefity

Płatny urlop

Elastyczne godziny

Napoje w biurze

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