Intermediate Application Developer

5 Months ago • 6 Years + • Data Analyst

Job Details

Company Description

Arηs is a fully independent group of companies specialized in managing complex IT projects and systems for large organisations, focusing on state-of-the-art software development, business intelligence and infrastructure services.

We are composed of 13 entities across 6 countries that are unified by the Arηs Group, with more than 1750 consultants.

This corporate structure enables us to respond quickly to market changes and customer requests, and to communicate and make decisions without layers of bureaucracy.

Our success can be attributed to the synergy among our nine complementary entities, combined with our methodologies, which are based on the Rational Unified Process (RUP) and the Scrum agile software development framework.

Established in 2016, the Greek entity Arηs Developments Hellas aims to extend Arηs Group activities dedicated to the European market providing high-quality services in Software Development, covering the entire application development lifecycle: starting with user requirements, business process redesign and specifications, to continue with development, testing and application maintenance.

Job Description

The candidate is going to be responsible for :

  •  Data collection: create pipelines to interact with internal and external databases, including web APIs. Design, develop, document and maintain processes for data collection, integration, transformation and dissemination including automation processes
  •  Data mining and data analysis: Design, develop, document and maintain data analytics and statistical analysis products, reports and surveys
  •  Data processing: Design, develop, document, maintain and ensure data quality, data harmonization and cleaning
  • Prediction: Development of predictive models, such as machine learning, to identify relevant features and predict future events
  •  Data reporting: Design, develop, document and maintain BI models, reports, dashboard, security, and automation
  • Data visualization: Design and build interactive and attractive visualizations of data
  • Collaborate with data architect/engineer to design, develop, document and maintain data architecture, data modelling and metadata
  • Facilitate analysis and integration processes on the overall data ecosystem, including data governance, by working with data providers to fill data gaps and/or to adjust source-system data structures
  • Participation in meetings with the project and data teams

Qualifications

  • Bachelor's plus 6 years of relevant experience.
  • Knowledge of Natural Language Processing libraries and techniques using Python
  • Creating reports, visualizations, and dashboards using Python (e.g. Databricks, Jupyter notebooks, voila dashboards) and Power BI
  • Development and data processing using Python for structured, semi-structured and unstructured data types and related file format (e.g. JSON, Parquet, Delta)
  • Advanced Power BI Online Services and best governance practices
  • Gathering business requirements and transforming it into data collection, integration and analysis processes
  • Knowledge of modelling libraries, including OLS regression, generalized linear models and machine-learning, in Python
  • Data modelling, principles and methods
  • Good knowledge of English equal to C1 level

 

Additional, desirable technology areas where above tasks are to be delivered include:

  • Advanced data and statistical analysis, techniques and tools using R
  •  Microsoft On-Prem and Azure Data Platform tools (such as Azure Data Factory, Azure Functions, Azure Logic Apps, SQL Server, ADLS, Azure Databricks, Microsoft Fabric/Power BI, Azure DevOps, Azure AI Services)
  • Databricks ecosystem, Apache Spark, Polyglot and Python and R data processing libraries
  • Knowledge of SQL, Power M, DAX,
  • Data governance and data management standards, policies, processes, metadata, quality
  • Data Lakes and Data Lakehouse architecture, concepts and governance
  • Master data and reference data management concepts
  • Business glossaries, data dictionaries, and data catalogues
  • DAMA Data Management best practices and standards
  • Web APIs and OpenAPI standard
  • Survey tool e.g. EU Survey

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