Data Analyst at BWG Foods
Dublin, County Dublin, Ireland -
Full Time


Start Date

Immediate

Expiry Date

31 Aug, 25

Salary

0.0

Posted On

31 May, 25

Experience

0 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

No

Skills

Relational Databases, Communication Skills, Excel

Industry

Information Technology/IT

Description

DATA ANALYST- PERMANENT FULL-TIME

BWG is seeking a highly analytical and detail-oriented Data Analyst to join our team on a permanent full-time basis. This role is ideal for someone passionate about uncovering insights from large datasets and driving data-informed decision-making across the business.
BWG Foods owns and operates the SPAR, EUROSPAR, MACE, Londis and XL brands in the Republic of Ireland, working in partnership with independent retailers with more than 1,000 stores serving local communities right across the country. The stores serve in excess of one million shoppers every single day.
The wholesale division of BWG Foods also includes BWG Foodservice, Corrib Food Products and Williams Gate, as well as Value Centre and 4 Aces, our nationwide network of Cash and Carry branches

EXPERIENCE & SKILLS FOR A DATA ANALYST:

  • Strong analytical and interpretive skills with a keen eye for detail.
  • Proficiency in data analysis tools and relational databases, including Microsoft SQL, R Studio, Diver BI, and Excel.
  • Experience working with large datasets and data mining techniques.
  • Excellent communication skills, with the ability to explain complex data clearly.
  • Highly organized, methodical, and a collaborative team player.
Responsibilities
  • Mine, manipulate, and analyse large datasets to extract actionable insights.
  • Interpret complex data and present trends and patterns to both technical and non-technical audiences.
  • Create compelling visualizations and dashboards to communicate findings effectively.
  • Design and implement strategies to improve data efficiency and accessibility.
  • Develop and maintain automated data pipelines and processes.
  • Monitor and report on key performance indicators (KPIs).
  • Ensure data quality, completeness, accuracy, and timeliness.
  • Identify and implement data validation and cleansing tools.
  • Collaborate with internal teams and external partners to support data-driven projects.
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