Senior Data Analyst (d/f/m) in Hamburg at LetMeShip
22529 Hamburg, Lokstedt, Germany -
Full Time


Start Date

Immediate

Expiry Date

16 Jun, 25

Salary

0.0

Posted On

16 May, 25

Experience

0 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

No

Skills

Good communication skills

Industry

Information Technology/IT

Description

YOUR MISSION

As a Data Analyst at LetMeShip, your mission is to harness the power of data to drive informed decision-making and optimize operational efficiencies. You will play a pivotal role in dealing with complex data constructs in our Data Lake, developing robust Data Pipelines, and creating insightful Data Visualizations. Your work will be integral to ensuring stakeholders are well-informed through accurate Reporting and thorough Documentation. Additionally, you will contribute to maintaining data integrity through diligent Data Cleaning efforts.

YOUR WAY TO US

You feel addressed and are interested in joining our team as Data Analyst (d/f/m)?
Please apply stating your earliest possible starting date! Alexander is looking forward to your application.

ABOUT US

ITA Logistics Group came into existence when LetMeShip and ParelParcel joined forces in 2023. We are the leading European multi carrier shipping provider dedicated to delivering any of our customers exactly the right carrier and service for their shipping need at any given time. With a strong heritage in the industry, our commitment to customer satisfaction and operational efficiency sets us apart in the market

Responsibilities
  • Data Lake Management: Oversee the organization, storage, and accessibility of data within the Data Lake infrastructure.
  • Data Pipeline: Develop and maintain efficient data pipelines to streamline the flow of information across systems.
  • Data Visualisation: Create meaningful and impactful visual representations of data using tools like Tableau.
  • Stakeholder Management: Collaborate effectively with stakeholders to understand requirements and deliver actionable insights.
  • Reporting: Generate regular reports that highlight key metrics and trends, supporting data-driven decision-making.
  • Documentation: Maintain comprehensive documentation of processes, datasets, and analyses to ensure transparency and reproducibility.
  • Data Cleaning: Implement processes to clean and preprocess data, ensuring accuracy and reliability for analytical purposes.
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