Vaga de parceiro

Data Quality & Governance Engineer - São Paulo / SP

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Detalhes da Vaga

  • Escolaridade Não Informado
  • Segmento Não Informado
  • Salário Não Informado
  • Área de AtuaçãoDiversos / Outros

O que você irá fazer

  • We are a venture-backed startup that is making a big impact on the environment, forever changing the landscape of eCommerce.
  • We are a remote-first company that is full of inspiring and friendly people.
  • We are currently searching for a Data Quality Engineer to join our fast-growing team.
  • This position is for someone located in São Paulo, Brazil who is able to come into the office in-person at least once weekly.
  • In this position you will have the opportunity to work with some of our biggest projects within the retail industry.
  • About You:You are a humble, passionate, and experienced engineer that is looking for a collaborative and analytical Data Quality Engineering role to support the execution of our product deliveries and client reporting services.
  • This comprises validating the data flow as a whole, from data sources to data consumers, including BI dashboards and ML models.
  • As our Data Quality Engineer, you are an extremely detail oriented, out-of-the-box problem solver with a commitment to doing high-quality work.
  • You will work with the Engineering, Product and Customer Success teams to support the flow of cleaned, quality data to ultimately drive customer success.
  • How You Will Make an Impact:Identify metrics used to measure data qualityEstablish data validations that cover both functional and domain-specific KPI dataMonitor data quality metrics and perform root cause analysis of data quality issues, taking appropriate steps to address any issuesMake sure that data quality processes are integrated into the data architectureSupport all the data governance initiativesUnderstand the data and KPI reporting requirements for clients, ensuring that the data quality initiatives alignSkills and Qualifications: (even if you do not meet these skills 100%, we still welcome you to apply)BSc or MSc Degree in Engineering, Mathematics, Physics, Computer Science or related field3+ years experience in data engineering and quality assessment rolesProficiency with Python and SQLBonus if experienced with DBTA strong understanding of data management concepts including data profiling and mappingSkilled in performing data quality assessments to identify data inconsistencies, inaccuracies and incompleteness in data productsStrong analytical skills to identify patterns, trends in data and data quality issuesGood understanding of data governance concepts including data privacy and securityA mindset of continuous improvement, identifying areas for improvement within the data quality process and workflowsAbility to troubleshoot and solve data quality issues, including identifying the root cause of problems and implementing effective solutionsAbove bar communication skills, both written and oral, to interface in a collaborative team environmentWell organized individual that pays close attention to detailAble to effectively prioritize in a fast-paced and fast-changing environmentBonus if you have experience integrating with large retail e-commerce sitesAbout Us:Bold Metrics, established in 2017, is a SaaS solution for retailers and brands to reduce returns, improve sustainability and supercharge their supply chain from the ground up.
  • Using a comprehensive set of machine learning and AI technologies to accurately capture customer body measurements, we help apparel brands unlock the power of body data to meet the demands of today''s increasingly personalized world.
  • We strive to create a place to work where we all feel safe, empowered, engaged and inspired.
  • We are an equal opportunity employer committed to offering employment that is based upon personal capabilities and qualifications without discrimination based on race, religion, color, national origin, gender, gender identity, sexual orientation, age, marital status, veteran status, or disability.
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  • Quantidade de Vagas 1
  • Jornada Não Informado
 

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