Interim Data Engineer

vor 3 Wochen

Basel, Schweiz GLONETPARTNERS Vollzeit

As a Data Engineer specializing in digital transformation projects, you will play a pivotal role in unlocking the value of data to drive innovation, improve decision-making, and fuel business growth. Your primary responsibility will be to understand and analyze available data, design data concepts for selected initiatives, and develop a comprehensive data strategy aligned with the organization's digital transformation goals.

Key Responsibilities:

  • Data Analysis: Conduct in-depth analysis of existing data sources, including structured and unstructured data, to gain insights into data quality, completeness, and relevance.
  • Data Modeling: Design and develop data models, schemas, and structures to organize and represent data in a way that supports business requirements and analytics needs.
  • Data Integration: Integrate disparate data sources, systems, and platforms to create a unified view of data, ensuring data consistency, accuracy, and accessibility across the organization.
  • Data Governance: Establish data governance frameworks, policies, and procedures to ensure data integrity, privacy, security, and compliance with regulatory requirements.
  • Data Strategy Development: Collaborate with stakeholders to define business objectives and identify opportunities for leveraging data to drive digital transformation initiatives.
  • Data Architecture Design: Design scalable and flexible data architectures, including data lakes, data warehouses, and data marts, to support current and future business needs.
  • Data Pipelines: Develop and implement data pipelines and ETL (Extract, Transform, Load) processes to automate data ingestion, transformation, and loading tasks.
  • Data Visualization: Work with data visualization tools and platforms to create insightful and actionable dashboards, reports, and visualizations that enable data-driven decision-making.
  • Data Quality Assurance: Implement data quality monitoring and validation processes to ensure data accuracy, consistency, and reliability throughout its lifecycle.
  • Collaboration: Collaborate with cross-functional teams, including data scientists, analysts, engineers, and business stakeholders, to align data initiatives with business objectives and priorities.

Qualifications:

  • Bachelor's degree in Computer Science, Information Systems, or related field; Master's degree preferred.
  • Proven experience in data engineering, data architecture, or related roles, preferably in a digital transformation or technology-driven environment.
  • Strong understanding of data management principles, techniques, and best practices, including data modeling, integration, governance, and quality assurance.
  • Proficiency in SQL and experience with relational databases, data warehouses, and big data platforms (e.g., Hadoop, Spark, Kafka).
  • Experience with data visualization tools (e.g., Tableau, Power BI) and programming languages (e.g., Python, R) for data analysis and visualization.
  • Knowledge of cloud platforms (e.g., AWS, Azure, Google Cloud) and experience with cloud-based data services (e.g., S3, Redshift, BigQuery) is a plus.
  • Excellent analytical, problem-solving, and communication skills, with the ability to translate complex technical concepts into business insights and recommendations.
  • Ability to work independently and collaboratively in a fast-paced, dynamic environment, with a strong commitment to delivering high-quality results on time and within budget.

Language: English, German

Duration: 6-12 months

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