This position is no longer open for applications

Data Engineer - Hiring ASAP

Start Date: ASAP
Duration: 6 months initially
Rate: £550 per day (Only subject to Employee Tax & NI)
Location: London based
Engagement Method: PAYE

Responsibilities

• Design, model, and implement data warehousing activities to deliver the data foundation that drives impact through informed decision making.
• Design, build and launch collections of sophisticated data models and visualisations that support multiple use cases across different products or domains.
• Collaborate with engineers, product managers and data scientists to understand data needs, representing key data insights visually in a meaningful way.
• Define and manage SLA for all data sets in allocated areas of ownership.
• Create and contribute to frameworks that improve the efficacy of logging data, while working with data infrastructure to triage issues and resolve.
• Determine and implement the security model based on privacy requirements, confirm safeguards are followed, address data quality issues, and evolve governance processes within allocated areas of ownership.
• Solve challenging data integration problems utilizing optimal ETL patterns, frameworks, query techniques, and sourcing from structured and unstructured data sources.
• Optimize pipelines, dashboards, frameworks, and systems to facilitate easier development of data artifacts.
• Influence product and cross-functional teams to identify data opportunities to drive impact.
• Work on problems of diverse scope where analysis of data requires evaluation of identifiable factors.
• Demonstrate good judgment in selecting methods and techniques for obtaining solutions.

Key Skills

• Requires five years of experience in the following:
• Features, design, and use-case scenarios across a big data ecosystem.
• Custom ETL design, implementation, and maintenance.
• Exploratory analysis across large and unstructured data sets.
• Data cleansing and normalisation.
• Presentation with historical and real time data visualisations.
• Object-oriented programming languages.
• Schema design and dimensional data modelling.
• Writing SQL statements.
• Analysing data to identify deliverable, gaps, and inconsistencies.
• Managing and communicating data warehouse plans to internal clients.
• MapReduce or MPP system.
• Python/Java.