SoftServe

Lead DBT Engineer

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SeniorZdalnieFull-time

#469140·Dodano 8 dni temu·2

Źródło: nofluffjobs.com

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Tech Stack / Keywords

Python Sparkdbt

Podsumowanie oferty

You will help transform the Agora data platform from a setup using Spark, Python, Airflow and Apache Iceberg into a modular architecture centered on dbt and Lakekeeper. The work includes data transformations, platform migration and supporting analytics use cases.

Wymagania

Strong experience in data engineering or analytics engineering.
Hands-on experience with dbt.
Solid knowledge of SQL and SQL-based transformation design.
Experience with modern data platform and warehouse/lakehouse concepts.
Practical experience with Apache Iceberg.
Experience with at least some of the following technologies: Spark, Python, Airflow, Starburst, Microsoft Fabric, Snowflake.
Understanding of data modeling, semantic layers and analytics-focused data design.
Experience with CI/CD, testing and data quality practices in data platforms.
Familiarity with lineage and technical documentation standards.
Ability to work in an open, modular architecture with separated storage and compute principles.
Understanding of cloud-first platform migration challenges and best practices.
Strong collaboration and communication skills.

Obowiązki

Support the migration of the Agora data platform to a cloud-first architecture.
Develop and maintain data transformation logic using dbt as the central business logic layer.
Refactor and consolidate logic distributed across Spark, Python and Airflow into a standardized dbt-based approach.
Work with Apache Iceberg as the core storage layer in the current and target architecture.
Contribute to implementing an open, modular platform built around Lakekeeper.
Support data ingestion workflows across Starburst, Microsoft Fabric and Snowflake.
Help build and maintain scheduling and orchestration processes using dbt and/or Microsoft Fabric.
Enable and improve data quality, lineage, documentation and CI/CD practices across the platform.
Collaborate on transitioning the semantic layer from Dremio to Starburst.
Support semantic modeling for analytics using Iceberg views stored in Lakekeeper.
Work with cross-functional stakeholders to reduce operational complexity and improve platform maintainability.
Contribute to developing a flexible data foundation prepared for future analytics and AI-driven use cases.

Benefity

Sport subscription.
Training budget.
Private healthcare.
International projects.
Free coffee.
Canteen.
Bike parking.
Free snacks.
Free parking.
In-house trainings.
Modern office.
No dress code.

Karta sportowa

Dofinansowanie szkoleń

Opieka zdrowotna

Napoje w biurze

Firmowa stołówka

Parking dla rowerów

Darmowe przekąski

Parking dla aut

Szkolenia wewnętrzne

SoftServe

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