Data Analyst SQL Python Tableau

1 month ago

London, Greater London, United Kingdom Capital On Tap Full time
About Capital On Tap

Capital On Tap is a dynamic and innovative company that values diversity and inclusivity. We're looking for a talented Growth Data Analyst to join our team and contribute to our rapid growth trajectory.

Job Description

We're seeking a skilled Growth Data Analyst to help us drive growth and impact through smart use of data and advanced analytics. As a key member of our Data team, you'll work closely with our data engineering team to productionize datasets and find innovative data sources to ingest.

Key Responsibilities
  • Find exciting commercial opportunities and turn them into real business growth using advanced analytical skills.
  • Create and maintain analytical data pipelines in DBT and Python to support ongoing analysis and facilitate incorporation into future BAU data processes.
  • Work with external partners to incorporate new data sets seamlessly.
  • Find innovative data sources and define ways to ingest the data, such as web scraping.
  • Collaborate with our data engineering team to productionize datasets.
Requirements
  • 2-4 years of experience as a data engineer or data analyst in a fast-paced environment (a startup/scale-up).
  • Strong analytical/quantitative skills and ability to cast business problems as analytical questions.
  • Strong SQL skills.
  • Experience with a programming language like Python or R, and dashboarding software such as Looker or Tableau would be beneficial.
What We Offer
  • Private Healthcare including dental and opticians services through Vitality.
  • Worldwide travel insurance through Vitality.
  • Anniversary Rewards (£250, £500, £750, 4-week fully paid sabbatical).
  • Salary Sacrifice Pension Scheme up to 7% match.
  • 28 days holiday (plus bank holidays).
  • Enhanced Parental Leave.
  • Cycle to Work Scheme.
  • Season Ticket Loan.
  • Dog Friendly Offices.
Interview Process

The interview process will consist of three stages: a 30-minute intro and values call with Talent Partner, a 30-minute SQL live-coding assessment followed by a 15-minute chat with Senior Analyst, and a 30-minute interview with Director of Data Science.

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