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Tech Stack
Tools & technologiesAirflowAmazon RedshiftAWSAzureBigQueryCloudDockerGoogle Cloud PlatformHadoopKafkaKubernetesPySparkPythonScalaSparkSQLTableau
About the role
Key responsibilities & impact- Lead the technical architecture of Data, Analytics and AI solutions for our clients, covering the full lifecycle from design to deployment:
- Design end-to-end data architectures: 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 (model registries, CI/CD for ML, monitoring).
- Lead technical decisions on cloud platforms (Azure, AWS, GCP) 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 the gap between data analysts, data engineers, and AI/ML engineers on complex projects.
- Contribute to internal knowledge base, toolkits, and delivery accelerators.
- Lead architecture workshops and discovery sessions with client stakeholders.
- Translate business requirements into scalable, robust technical blueprints.
- Present architecture decisions to both technical teams and executive audiences.
- Support pre-sales and proposal efforts with technical scoping and solution design.
- Provide internal training and knowledge-sharing sessions with the team.
- Support the Head of Practice on business development and internal capability initiatives.
Requirements
What you’ll need- Master’s degree in Computer Science, Data Engineering, Software Engineering, Applied Mathematics, or a related field.
- Full proficiency in English + 1 additional language (French, Arabic, Spanish, 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.
- Proven hands-on experience designing large-scale data platforms: data lake, lakehouse, or warehouse architectures (Databricks, Snowflake, BigQuery, Azure Synapse, Redshift).
- Strong command of SQL and at least one of Python, Scala, or Spark for data processing and transformation.
- Experience with Big Data ecosystems: Hadoop, Spark, PySpark, Hive, or equivalent.
- Familiarity with streaming and real-time architectures (Kafka, Flink, Spark Streaming).
- Proven hands-on experience with ML lifecycle tooling: MLflow, Kubeflow, SageMaker, Azure ML, or equivalent.
- Experience architecting MLOps pipelines: model versioning, CI/CD for ML, monitoring and drift detection.
- Exposure to GenAI and LLM integration patterns (RAG architectures, vector databases, prompt pipelines).
- Proven hands-on experience with orchestration and transformation tools: Airflow, dbt, or equivalent.
- Proven hands-on experience with container technologies: Docker, Kubernetes.
- Proven hands-on experience with versioning software: Git, GitHub, GitLab.
- Proven hands-on experience deploying solutions in cloud ecosystems: AWS, Azure, or Google Cloud.
- Knowledge of data governance frameworks: data catalogs, lineage tracking, access control, and data quality management.
- Exposure to BI and data visualization platforms (Power BI, Tableau, Looker) and semantic layer design.
- Strong ability to work and collaborate with a variety of stakeholders across technical and business functions.
Benefits
Comp & perks- A competitive salary.
- A great working environment.
- A steep learning curve with interesting and diverse topics to work on.
- A healthy work-life balance.
- Health insurance benefits.
ATS Keywords
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Hard Skills & Tools
data architecturedata lakeslakehousesdata warehousesMLOpsSQLPythonScalaSparkBig Data
Soft Skills
technical mentorshipcollaborationcommunicationleadershipproblem-solvingstakeholder engagementpresentation skillsbusiness developmentknowledge sharingtraining
Certifications
Master’s degree in Computer ScienceMaster’s degree in Data EngineeringMaster’s degree in Software EngineeringMaster’s degree in Applied Mathematics