Data Engineering Consultant

4 weeks ago

Allen Park, Michigan, United States Mindlance Full time
Data Engineering Consultant

This is a key role in our Industrial Systems IT Transformation effort, focusing on designing and deploying Data Centric Architecture in GCP for Materials Management platform. The ideal candidate will have experience in designing and implementing data-centric solutions on Google Cloud Platform (GCP) using various GCP tools.

  • Design and implement data-centric solutions on GCP using Big Query, Google Cloud Storage, Cloud SQL, Memory Store, Dataflow, Dataproc, Artifact Registry, Cloud Build, Cloud Run, Vertex AI, Pub/Sub, and GCP APIs.
  • Build ETL pipelines to ingest data from heterogeneous sources into our system.
  • Develop data processing pipelines using programming languages like Java and Python to extract, transform, and load (ETL) data.
  • Create and maintain data models, ensuring efficient storage, retrieval, and analysis of large datasets.
  • Deploy and manage databases, both SQL and NoSQL, such as Bigtable, Firestore, or Cloud SQL, based on project requirements.
  • Optimize data workflows for performance, reliability, and cost-effectiveness on the GCP infrastructure.
  • Implement version control and CI/CD practices for data engineering workflows to ensure reliable and efficient deployments.
  • Utilize GCP monitoring and logging tools to proactively identify and address performance bottlenecks and system failures.
  • Troubleshoot and resolve issues related to data processing, storage, and retrieval.
  • Promptly address code quality issues using SonarQube, Checkmarx, Fossa, and Cycode throughout the development lifecycle.
  • Implement security measures and data governance policies to ensure the integrity and confidentiality of data.
  • Collaborate with stakeholders to gather and define data requirements, ensuring alignment with business objectives.
  • Develop and maintain documentation for data engineering processes, ensuring knowledge transfer and ease of system maintenance.
  • Participate in on-call rotations to address critical issues and ensure the reliability of data engineering systems.
  • Provide mentorship and guidance to junior team members, fostering a collaborative and knowledge-sharing environment.

Requirements:

  • 8 years of professional experience in data engineering, data product development, and software product launches.
  • At least three of the following languages: Java, Python, Spark, Scala, SQL, and experience in performance tuning.
  • 4 years of cloud data/software engineering experience building scalable, reliable, and cost-effective production batch and streaming data pipelines using data warehouses like Google BigQuery, workflow orchestration tools like Airflow, relational database management systems like MySQL, PostgreSQL, and SQL Server, real-time data streaming platforms like Apache Kafka and GCP Pub/Sub, microservices architecture, REST APIs, and DevOps tools like Tekton, GitHub Actions, Git, GitHub, Terraform, Docker, and project management tools like Atlassian JIRA.
  • Automotive experience is preferred.
  • Support in an onshore/offshore model is preferred.
  • Excellent problem-solving and prevention skills.
  • Knowledge and practical experience of agile delivery.

Preferred experience includes IDOC processing, APIs, and SAP data migration projects, as well as experience working in SAP S4 Hana environments.

Education: Requires a bachelor's or foreign equivalent degree in computer science, information technology, or a technology-related field.

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