Data Engineer Leader

6 days ago

Cape Town, Western Cape, South Africa LexisNexis South Africa Shared Services (Pty) Ltd Company Full time
About the Role

We are seeking a skilled Senior Data Engineer I to join our team at LexisNexis South Africa Shared Services (Pty) Ltd Company.

As a senior machine learning operations engineer, you will work on new product development in a small team environment writing production code in both run-time and build-time environments. You will help propose and build data-driven solutions for high-value customer problems by discovering, extracting, and modeling knowledge from large-scale natural language datasets.

You will prototype new ideas, collaborating with other data scientists as well as product designers, data engineers, front-end developers, and a team of expert legal data annotators. You will get the experience of working in a start-up culture with the large datasets and many other resources of an established company.

  • Develop and implement a strategy for continuous improvement of our Machine Learning Ops including versioning, testing, automation, reproducibility, deployment, monitoring, and data privacy
  • Develop and report on ML Ops metrics such as deployment frequency, lead time for changes, mean time to restore, and change failure rate
  • Collaborate with data scientists, data engineers, API engineers, and the dev ops team
  • Build scalable data ingestion and machine learning inference pipelines
  • Scale up production systems to handle increased demand from new products, features, and users
  • Provide visibility into the health of our data platform (comprehensive view of data flow, resources usage, data lineage, etc) and optimize cloud costs
  • Automate and handle the life-cycle of the systems and platforms that process our data
Requirements
  • Masters degree in Software Engineering, Data Engineering, Computer Science or related field
  • 5 years of relevant work experience
  • Strong Scala and Python background
  • Experience with Apache Spark and/or Ray
  • Knowledge of AWS, GCP, Azure, or other cloud platform
  • Knowledge of current principles and frameworks for ML Ops
  • Experience with ML Ops technologies such as ML Flow, DVC, Grafana, DataHub, Databricks
  • Experience with machine learning technologies such as PyTorch, TensorFlow, AWS Sagemaker
  • Experience with CI/CD pipelines, including Jenkins or Git Actions
  • Experience with Docker containerization or Kubernetes orchestration
  • Experience in improving data security and privacy, and managing and reducing cloud costs
  • Knowledge of API development and machine learning deployment
About Us

We promote a healthy work/life balance across the organization, with various flexible and remote working options available to employees.

LexisNexis Legal & Professional is proud to be an equal-opportunity employer. We are committed to equal opportunity employment regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status.

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