Senior Data Engineer - ETL & Big Data Pipelines

Truist

Charlotte (NC)

Vor Ort

USD 110.000 - 150.000

Vollzeit

Vor 11 Tagen

Eine vollständige Bewerbung in einer Minute

Maßgeschneiderter Lebenslauf und Anschreiben – versandbereit.

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Benefits dieser Stelle

Medical benefits
401k plan
Paid vacation

Zusammenfassung

Truist is seeking a data engineer to build, optimize, and maintain data pipelines and the enterprise data ecosystem. The role involves developing data models, architecture documents, and APIs, and advancing ETL processes across the data stack.

The candidate will automate data preparation tasks, collaborate with technology teams, and lead small data engineering projects with moderate risk. Based in Charlotte, NC, onsite at least three days weekly, with potential hybrid options.

Qualifikationen

  • Bachelor's degree in Computer Science, Systems Engineering or related technical field.
  • 5+ years of progressive software engineering or development experience focusing on data warehousing, data integration, ETL and big data concepts.
  • Experience with SQL, ETL architectures and data integration tools, Informatica, shell scripting, and SDLC artifacts.

Aufgaben

  • Build, optimize, and maintain data pipelines and data ecosystem for enterprise data access.
  • Develop data models, architecture documents, and APIs.
  • Automate repeatable data preparation and integration tasks.
  • Partner with technology teams to design, test, and implement end-to-end data solutions.
  • Lead small data engineering projects with manageable risks.

Kenntnisse

Data modeling
Problem solving
Data analysis

Ausbildung

Bachelor's degree in Computer Science or related field

Tools

SQL
Informatica
Shell scripting

Jobbeschreibung

Truist is seeking a data engineer to build, optimize, and maintain data pipelines and the enterprise data ecosystem. The role involves developing data models, architecture documents, and APIs, and advancing ETL processes across the data stack.

The candidate will automate data preparation tasks, collaborate with technology teams, and lead small data engineering projects with moderate risk. Based in Charlotte, NC, onsite at least three days weekly, with potential hybrid options.

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