Infomineo

Infomineo

Infomineo is a global leader in brainshoring services, offering business research, data analytics, graphic design, and content services. They provide customized research solutions, data transformation, and professional design services to help clients m...

Professional Services
251-1K
Founded 2011

Description

  • Lead the technical architecture of data, analytics, and AI solutions from design through deployment.
  • Design end-to-end data architectures including data lakes, lakehouses, warehouses, and streaming pipelines.
  • Define standards for data modeling, storage, ingestion, and transformation across client engagements.
  • Architect MLOps and AI deployment infrastructure, including model registries, CI/CD for ML, monitoring, and drift detection.
  • Lead technical decisions on cloud platforms and open-source tooling.
  • Define best practices and reusable frameworks for data engineers, analysts, and data scientists.
  • Act as a technical mentor and reviewer for cross-functional project teams.
  • Bridge collaboration between data analysts, data engineers, and AI/ML engineers on complex projects.
  • Contribute to internal knowledge bases, toolkits, and delivery accelerators.
  • Lead architecture workshops and discovery sessions with client stakeholders.
  • Translate business requirements into scalable technical blueprints and present architecture decisions to technical and executive audiences.
  • Support pre-sales and proposal efforts with technical scoping and solution design.
  • Provide internal training and knowledge-sharing sessions.
  • Support business development and internal capability initiatives.

Requirements

  • Master’s degree in Computer Science, Data Engineering, Software Engineering, Applied Mathematics, or a related field.
  • Full proficiency in English plus one additional language such as French, Arabic, Spanish, or German.
  • 6+ years of technical experience in data architecture or a closely related field.
  • Proven track record in a consulting or multi-client services environment.
  • Hands-on experience designing large-scale data platforms such as Databricks, Snowflake, BigQuery, Azure Synapse, or Redshift.
  • Strong command of SQL and at least one of Python, Scala, or Spark for data processing and transformation.
  • Experience with Big Data ecosystems such as Hadoop, Spark, PySpark, or Hive.
  • Familiarity with streaming and real-time architectures such as Kafka, Flink, or Spark Streaming.
  • Hands-on experience with ML lifecycle tooling such as MLflow, Kubeflow, SageMaker, or Azure ML.
  • Experience architecting MLOps pipelines, including model versioning, CI/CD for ML, monitoring, and drift detection.
  • Exposure to GenAI and LLM integration patterns such as RAG architectures, vector databases, and prompt pipelines.
  • Hands-on experience with orchestration and transformation tools such as Airflow or dbt.
  • Hands-on experience with Docker and Kubernetes.
  • Hands-on experience with Git, GitHub, or GitLab.
  • Hands-on experience deploying solutions in AWS, Azure, or Google Cloud.
  • Knowledge of data governance frameworks including data catalogs, lineage tracking, access control, and data quality management.
  • Exposure to BI and data visualization platforms such as Power BI, Tableau, or Looker, including semantic layer design.
  • Ability to analyze complex problems, define architectural options, and drive decisions.
  • Strong collaboration skills across technical and business stakeholders.
  • Excellent communication skills to translate complex technical architectures into business implications.
  • High autonomy, attention to detail, and ability to manage multiple client engagements simultaneously.

Benefits

  • Competitive salary.
  • Great working environment.
  • Steep learning curve with interesting and diverse topics.
  • Healthy work-life balance.
  • Health insurance benefits.

Interested in this position?

Apply directly on the company website

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