Databricks Data Engineer / Developer (PL 866)

๐Ÿข Paralucent ยท all Paralucent jobs
๐Ÿ“ Poland
๐Ÿ“… Posted 2026-08-12 ยท via Himalayas
๐Ÿท Data-Engineering,Databricks-Developer,ETL-ELT-Development,Data-Pipeline-Development,Cloud-Data-Engineering,Senior-Databricks-Engineer,Senior-Databricks-Developer,Data-Engineering-(Databricks),Azure-Databricks-Developer,Senior-Databricks-Architect
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Location: Remote within Canada

Client: Consulting Client
Contract Duration: 6 months contract

MUST HAVE atleast 3+ years of hands-on Databricks development experience.
Overview

Our consulting client is seeking a Databricks Data Engineer / Developer to support a strategic Enterprise Data Platform (EDP) transformation initiative. The organization is modernizing its enterprise data landscape and building a next-generation data platform leveraging Databricks and modern cloud-based architecture. This role will play a key part in designing, developing, and implementing scalable data solutions that support enterprise reporting, analytics, AI initiatives, and future data-driven capabilities.

The ideal candidate will possess strong data engineering expertise, hands-on Databricks development experience, and a solid understanding of ETL/ELT processes, data integration, and modern data architecture . This individual will work closely with data architects, project managers, analysts, and business stakeholders to deliver high-quality data solutions within a rapidly evolving environment.
Key Responsibilities

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Design, develop, and maintain data pipelines within the Enterprise Data Platform (EDP) .

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Build and optimize ETL/ELT processes to support data ingestion, transformation, and integration requirements.

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Make use of an Agentic approach to development and ensure that output matches development standards.

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Develop scalable and reusable data solutions using Databricks and cloud-based data technologies .

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Support migration and modernization activities from HANA environments to a modern data platform .

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Collaborate with Data Architects to implement scalable data models and platform solutions.

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Develop data transformation logic and workflows to support business and analytics requirements.

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Ensure data quality, integrity, consistency, and performance across platform solutions.

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Troubleshoot and resolve data-related issues, bottlenecks, and performance concerns.

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Participate in code reviews, testing, deployment, and release activities.

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Work closely with business and analytics teams to understand data requirements and deliver fit-for-purpose solutions.

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Contribute to platform best practices, documentation, and continuous improvement initiatives.

Requirements

MUST HAVE atleast 3+ years of hands-on Databricks development experience.
Required Qualifications

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3+ years of hands-on Databricks development experience .

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4+ years of overall Data Engineering, ETL, or Data Integration experience.

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Strong experience building ETL/ELT data pipelines and transformation processes.

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Proven experience working with large and complex datasets.

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Experience with Agentic frameworks and AI-assisted coding is a value add.

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Experience developing data solutions within cloud-based platforms.

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Solid understanding of data warehousing, data lake, and lakehouse concepts.

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Experience working in Agile delivery environments.

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Strong problem-solving and analytical skills.

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Excellent communication and collaboration abilities.

Preferred Qualifications

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Experience supporting large data platform initiatives.

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Experience in significant data migration efforts.

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Experience with Azure Data Services and Databricks Lakehouse architecture.

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Experience with modern data engineering frameworks and best practices.

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Exposure to AI, GenAI, Machine Learning, or advanced analytics initiatives.

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Experience working in large enterprise or consulting environments.

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Knowledge of data governance, metadata management, and data quality frameworks.

Technical Knowledge
Required

- Databricks

- ETL / ELT Development

- Data Engineering

- Data Integration

- SQL

- Python

- Data Pipeline Development

- Data Transformation

- Data Warehousing Concepts

- Agile Delivery

Preferred

- Azure Data Factory

- Delta Lake

- Spark / PySpark

- Azure Synapse

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