Data Engineer

110 - 130 PLN/ godz./ godz.B2BB2B (netto)

MidZdalnieFull-time·B2B

#479902·Dodano wczoraj·0

Źródło: nofluffjobs.com

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Tech Stack / Keywords

Python SQL Apache Spark PySpark Databricks Snowflake AWS AzuredbtETL ELTData modelingApache AirflowDatabricks WorkflowsCI/CD GitData GovernanceData Quality

Podsumowanie oferty

Build and maintain scalable data pipelines and lakehouse infrastructure powering analytics, machine learning, and AI agent platforms. Ensure reliable data flows from operational sources into analytical layers, knowledge graphs, and AI workflows using SQL, Python, Databricks, Snowflake, AWS, Azure, and dbt.

Wymagania

At least 3 years of hands-on experience as a Data Engineer building production data pipelines.
Strong proficiency in SQL and Python, with practical experience in distributed data processing using Databricks and PySpark.
Hands-on experience with modern data platforms (Databricks, Snowflake, AWS, or Azure) and transformation or orchestration tools (dbt, Apache Airflow, or Databricks Workflows).
Solid understanding of data modeling concepts, including dimensional modeling and lakehouse architecture, and CI/CD best practices using Git.
Detail-oriented approach to data reliability, performance tuning, and pipeline monitoring.

Obowiązki

Design, build, and maintain scalable batch and streaming ETL/ELT pipelines in cloud environments using Databricks, Snowflake, AWS, or Azure.
Transform raw structured and semi-structured data into curated analytical models using SQL, Python, and dbt.
Implement automated data quality checks, schema validation, logging, and pipeline observability.
Collaborate with Ontology, Knowledge Graph, and Data Science teams to prepare datasets for graph ingestion and ML feature stores.
Enforce data governance, lineage, and security standards, including role-based access control, PII handling, and GDPR compliance.

Inne informacje

During onboarding, working hours may be adjusted to overlap with US hours, until 7:00 PM at the latest.

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