Enterprise Data Architect with Python Expertise

hace 2 semanas

Medellín, Antioquia, Colombia Endava A tiempo completo

At Endava, we are harnessing technology to drive meaningful change. By combining world-class engineering, industry expertise, and a people-centric mindset, we consult and partner with leading brands to create dynamic platforms and intelligent digital experiences.

Data Engineer Job Description

Our data team has expertise across engineering, analysis, architecture, modeling, machine learning, artificial intelligence, and data science. This discipline is responsible for transforming raw data into actionable insights and enabling data-driven decision-making and innovation through advanced analytics and predictive modeling.

As a Senior Data Engineer at Endava, you will be responsible for developing and implementing data pipelines, collaborating with data architects, and ensuring data quality and integrity. You will also support data migration projects and contribute to agile development processes.

  • Collaborate with the Data Analyst/Data Scientist to understand evolving needs and define the data processing flow or interactive reports.
  • Discuss with stakeholders from other teams to better understand how data flows are used within the existing environment.
  • Propose solutions for cloud-based architecture and deployment flow.
  • Design and build processes, data transformation, and metadata to meet business requirements and platform needs.
  • Design and propose solutions for the Relational and Dimensional Model based on platform capabilities.
  • Develop, maintain, test, and evaluate big data solutions.
  • Focus on production status and data quality of the data environment.
  • Pioneer initiatives around data quality, integrity, and security.

Requirements

  • +5 years of experience in Data Engineering.
  • Proficiency in Apache Spark.
  • Proficiency in Python.
  • Some experience leading IT projects and stakeholder management.
  • Experience implementing ETL/ELT process and Data pipelines.
  • Experience with Snowflake.
  • Strong SQL scripting experience.
  • Background and experience with cloud data technologies and tools.
  • Familiar with data tools and technologies like Spark, Hadoop, Apache Beam, Dataproc or similar.
  • BigQuery, Redshift, or other Data warehouse tools.
  • Real-time pipelines with Kinesis or Kafka.
  • Batch processing.
  • Serverless processing.
  • Strong analytic skills related to working with structured and unstructured data sensibilities.

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