Data Profiling Associate

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Employer: HRS Romania
Domain:
  • IT Software
  • Job type: full-time
    Job level: 1 - 5 years of experience
    Location:
  • BUCHAREST
  • Updated at: 28.06.2021
    Remote work: On-site
    Short company description

    Moving forward is impossible without the initial drive to do things differently. Our business is all about the people we come across, whether it's in our everyday interactions or in our vision for the brand.

    Requirements

    - Proven experience Python scripting for data processing;
    - Understanding SQL querying;
    - Having a background in working with data;
    - R/Power Query experience is a plus
    - Background in audit, banking, internal reporting, RPA, or analysis of data is a nice to have criteria;
    - Knowledge of Data Profiling best practices is nice to have;
    - Knowledge of Data Quality concepts, metrics, technical rules represents a plus;
    - Tools: BI (Snowflake, Power BI, Tableau) are nice to have.

    Responsibilities

    - Review source system data and provide a comprehensive understanding of its structure, content and interrelationships;
    - Evaluate technical rules on the source system data and identify data quality issues in the source system data;
    - Evaluate the source data feed’s fit against a designed and documented ELT interface;
    - Work with engineering individuals to create semi-automatic/automatic processes that are integrating the data;
    - Collect descriptive statistics regarding the source data;
    - Collect data types, lengths and recurring patterns;
    - Label data using keywords and/or descriptions;
    - Perform data quality assessments;
    - Assess the distribution of data;
    - Identify functional dependencies;
    - Perform inter-table analysis;
    - Map source data for ingestion into the staging area of the warehouse
    - Evaluate applicability of business rules on the source system data related to specific business processes;
    - Automate any repetitive activity regarding all the above responsibilities where possible.

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