Data engineer

Data engineer
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Data engineer
Data engineer
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5Data engineer resume examples found

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Experience level

Data engineer

Experienced

Wrote the most complex ETL (Extract / Transform / Load) processes, designs database systems, and developed tools for real-time and offline analytic processing. Troubleshoot software and processes for data consistency and integrity. Led the integration of highly complex and large-scale data from a variety of sources for business partners to generate insight and make decisions.

  • Translated business specifications into design specifications and code.
  • Established analytical rigor and methods for writing complex programs, ad hoc queries, and reports; ensured all code is structured and documented and is easy to maintain and reuse.
  • Partnered with internal clients and leaders to gain an expert understanding of highly strategic, high-risk business functions and informational needs.
  • Worked closely with technical and data analytics experts across the business to implement data solutions.
  • Acted as the highest point of escalation for data analysis and served as a technical consultant for the client.
  • Created an analytics-driven environment by gathering requirements, assessing gaps, and building roadmaps and architectures.
  • Educated and developed junior data engineers on the team while applying quality control to their work and increasing their knowledge in specialized Data Engineering techniques and processes.
  • Tested and implemented highly complex new software releases through regression testing. Identified issues and engaged with vendors to resolve and elevate software into production.
  • Turned raw data into usable data pipelines and built data tools and products for effort automation and easy data accessibility.
  • Diagnosed the existing architecture, data maturity, and identify gaps.
  • Built data assets that enhance the quality of overall data structures by implementing the data science program.
  • Identified gaps and implement solutions for data security, quality, and automation of processes.

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Data engineer

Entry level

Automated data ingestion procedures and improved overall reporting efficiency by 40% with the introduction of custom-built data views and reports. Collaborated with stakeholders and supervisor to define requirements and deliver tailored solution.

  • Met with supervisor to outline process improvement strategy.
  • Collaborated with engineering colleagues to develop and test algorithms designed to replace manual data ingestion, storage, and assessment operations.
  • Liaised with stakeholders to provide updates and integrate feedback as needed.
  • Obtained leadership approval and facilitated integration of new program utilizing SQL database and Google Analytics API technology.

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Data engineer

Senior

Directed operations and supported companywide initiatives while leading team of 20 data engineers. Handled all aspects of performance management while championing continuous improvement.

  • Delegated process development and database management tasks among engineers.
  • Led interviews, onboarding, and training efforts to build and maintain a proficient development team while cultivating a collaborative and efficient work environment.
  • Partnered with stakeholders to drive large-scale initiatives including migration to cloud-based integration software.

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Data engineer

Experienced

Designed and implemented real-time data pipeline to parse structured data from 25+ data sources using Kafka and PySpark applications. Utilized cross-functional collaboration to meet delivery deadlines.

  • Gathered team of data engineers, programmers, and software architects.
  • Strategized improved methods of collecting and storing large data sets.
  • Researched, assessed, and selected third party program solutions for optimized integration and utilization.
  • Trained department leaders and colleagues on how to integrate new applications and workflows for optimal results.

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Data engineer

Experienced

Saved enterprise technology company $900K+ in expenses over 1-year timeframe via migration initiative. Oversaw project planning, database integration, and engineering operations as project leader.

  • Petitioned transfer to more streamlined database management software to senior leadership for approval.
  • Held strategy meetings to define requirements and outline migration steps.
  • Facilitated data transfer tasks from enterprise system to MongoDB cloud-based solution for improved accuracy, efficiency, and storage capacity.
  • Drafted and distributed database management guidelines and best practices.

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