Data Analyst


Premium Job From Nigel Frank International

Recruiter

Nigel Frank International

Listed on

18th October 2021

Location

London

Salary/Rate

Negotiable

Salary Notes

Negotiable

Type

Permanent

Start Date

ASAP

This job has now expired please search on the home page to find live IT Jobs.

Data Analyst- 3-6 month contract- Fully remote (Inside IR35) £300-£400 per dayRequirement:Manage and oversee the data pipeline that is feeding reporting and ML models (tech stackbased on Python/Airflow, Dremio)Interface with Architecture and Dev teams to facilitate development of the tech stacks andadditional data sources Use Python (main libraries such as pandas, Pyodbc, sqlalchemy, airflow etc) to develop customconnection and data feeds through 3rd party APIs Use SQL scripting to manipulate and extract data from large relational databases & automatethe process for importing data from multiple sources and various file formats. (Flat files / ODBC/ OLDB etc). Interface with Data science team in order to enable Machine Learning projects / capabilities(make right data available)Deal confidently with different data sources and data models Being a key player to support the data project roadmap spanning all stages of the data valuechain: from data architecture to data engineering, data processing and model designKnowledge and ExperienceBachelor's degree in a quantitative field (math, statistics, comp. science, engineering,economics, etc.). Master's degree a plus Mid-level experience of relevant data environments such as MS SQL Server 2008/2016Expert-level experience of SQL Server programming/scripting experience Experience in programming DAG (Direct Acyclic Graphs) in Airflow 2 years' experience in programming with python or similar languages Minimum of 2/3 years in similar role or capacity required, working across different markets asbusiness partner.Experience or academic background on data models and relational DB schemas Attention to detail and data driven analytical & problem-solving skillsAbility to manage and prioritize own workload and escalate potential risk to the line manage

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