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Ford Motor Company
Ford Motor Company
H1B vīzas sponsorsKonsultācijasLoģistikaMārketings
Ford Motor Company ir Amerikas Savienotajās Valstīs bāzēts automobiļu ražotājs, kura vēsture aizsākās 1903. gadā. Papildus transportlīdzekļu izstrādei un ražošanai uzņēmums paplašina savu darbību mobilitātes pakalpojumu, digitālās pieredzes un programmatūras jomā. Ford darbība ietver arī ilgtspējas iniciatīvas un vides mērķu sasniegšanu, atspoguļojot pieeju, kas apvieno transportu, inovācijas, ietekmi uz kopienu un atbildīgu uzņēmējdarbības praksi.
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Vakances uzņēmumā

Full-Stack Data Engineer at Ford

Build scalable GCP data pipelines and platforms for Ford’s enterprise technology organization. Support governance, security, automation, and performance improvements.

INIndijaHibrīdiPilna slodzeVidējais līmenisVecākais speciālistsNepieciešamā Valoda: angļuDatu inženieris
BigQueryGoogle Cloud PlatformJavaMākonisMikropakalpojumiMySQLNoSQLPostgresPythonSQLTerraform

Apraksts

  • Create and maintain scalable ingestion and curation pipelines from varied data sources.
  • Standardize and improve data quality so it is ready for analytics.
  • Develop efficient data pipelines with Python, SQL, and DBT or Dataform.
  • Support end-to-end development and dependable data movement from source to insight.
  • Build and operate GCP data platforms using BigQuery, Dataflow, Pub/Sub, and Cloud Functions.
  • Apply data governance policies, access controls, and cloud security practices.
  • Manage data workflows and provision cloud infrastructure with Astronomer and Terraform.
  • Improve pipeline and storage performance, scalability, efficiency, resource use, and cost effectiveness.
  • Work with data and application architects, service owners, and cross-functional teams to establish practices, design patterns, and frameworks.
  • Automate platform operations to strengthen reliability, data quality, and efficiency.
  • Explain complex technical decisions to technical and non-technical stakeholders.
  • Find ways to improve the data platform and extend its capabilities.
  • Turn business needs into effective data asset designs and efficient code.
  • Document data engineering processes and encourage knowledge sharing.

Prasības

  • Bachelor’s degree in computer science, information technology, information systems, data analytics, or a related area, or an equivalent combination of education and experience.
  • Five to seven years in data engineering or software engineering, including at least two years building and deploying cloud data platforms; GCP experience is preferred.
  • Strong command of SQL, Java, and Python.
  • Hands-on experience designing and deploying cloud data pipelines with GCP services such as BigQuery, Dataflow, and DataProc.
  • Understanding of service-oriented architecture and microservices.
  • Experience with relational databases such as PostgreSQL and MySQL, NoSQL databases, and columnar databases such as BigQuery.
  • Knowledge of cloud data governance frameworks, encryption, and data masking.
  • Familiarity with CI/CD pipelines, infrastructure as code tools such as Terraform and Tekton, and automation frameworks.
  • Strong analytical and problem-solving abilities, including troubleshooting complex data platform and microservices issues.
  • Experience monitoring and optimizing costs and compute resources for GCP services such as BigQuery, Dataflow, Cloud Run, and DataProc.
  • Interest in data, innovation, and ongoing learning.

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Advocate Aurora Health

Remote Pharmacist Informatics Analyst, Medication Build

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Veselības apdrošināšanaVeselības aprūpe
USAmerikas Savienotās ValstisALAlabamaAKAļaskaAZArizonaFLFloridaIDAidahoILIlinoisaIAAiovaKSKanzasaKYKentukiLALuiziānaMEMeinaMIMičiganaMSMisisipiMOMisūriMTMontānaNENebraskaNVNevadaNHŅūhempšīraNMŅūmeksikaNCZiemeļkarolīnaNDZiemeļdakotaOHOhaioOKOklahomaPAPensilvānijaSCDienvidkarolīnaSDDienviddakotaTNTenesīTXTeksasaUTJūtaVAVirdžīnijaWVRietumvirdžīnijaWIViskonsinaWYVaiominga
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