Data Engineer

3 miesięcy temu

Kraków, Polska GPC Global Technology Center Pełny etat

Position Purpose

The Data Engineer is a technical role responsible for designing, developing, and maintaining data pipelines. The pipelines will be realized in alignment with the future data architecture and the engineer will collaborate in cross-functional teams to gather requirements and develop the conceptual data models. This role plays a crucial part in driving data-driven decision-making across the organization, ensuring data availability, quality, and accessibility for various business needs.

Responsibilities

Data Pipeline Development

  • Design, model, develop and maintain data pipelines to ingest, store, process, and present data.
  • Ensure data quality, accuracy, and consistency.
  • Collaborate with data architects to ensure data pipelines align with the overall data architecture strategy.

Data Transformation and Integration

  • Perform data transformation tasks, including data cleansing, enrichment, and aggregation, to prepare data for analytics and reporting.
  • Integrate data from structured and unstructured sources, ensuring compatibility and alignment with data models and business requirements.
  • Automate data transformation processes to improve efficiency.

Data Quality Assurance

  • Implement and maintain data quality checks and validation processes to identify and resolve data anomalies and errors.
  • Monitor data pipelines for data quality issues and implement data quality improvements.
  • Collaborate with business stakeholders to define data quality requirements.

Data Modelling and Schema Design

  • Collaborate with data architects and data scientists to design and implement data models, schemas, and structures.
  • Ensure that data models support business reporting and analytics needs while optimizing query performance.
  • Maintain data dictionaries and metadata to document data structures and relationships.

Performance Optimization

  • Optimize data storage, retrieval, and query performance by implementing indexing, partitioning, and caching strategies.
  • Monitor data processing performance and address bottlenecks as they arise.
  • Stay updated with best practices in data processing performance tuning.

Documentation and Knowledge Sharing

  • Create and maintain documentation for data pipelines, data transformation processes, and data integration procedures.
  • Foster a culture of knowledge sharing within the data engineering team and across the organization.

Collaboration and Stakeholder Engagement

  • Collaborate effectively with cross-functional teams, data stakeholders, and business units to understand data requirements and deliver data solutions that meet business needs.
  • Communicate technical concepts and data solutions to non-technical stakeholders in a clear and understandable manner.

Requirements

Essential:

  • Commercial experience of DataBricks, SQL, Python, Power BI
  • Experience in data engineering, including designing and developing data pipelines for retrieval / ingestion / presentation / semantics in an Azure environment.
  • Effective communication and collaboration skills to work with cross-functional teams and gather data requirements.
  • Skills in data modelling (both structured and unstructured data)

Desirable:

  • Power Automate
  • Data optimization for performance, scalability, and efficiency.
  • Experience in automotive/distribution sector

Benefits nad Perks

Location

Krakow/Hybrid

 

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