Position Summary:

We are seeking a proactive and intellectually curious Data Engineer with a strong background in Azure, Databricks, PySpark and Lakehouse architecture to join our innovative team based in Canada. In this role, you will collaborate closely with a multidisciplinary team to construct robust data pipelines driving advanced analytic solutions. These solutions will empower our SapienX clients to elevate their data-driven decision-making capabilities. As an Azure Data Engineer, you must possess a profound understanding of data architecture, engineering, analysis, and modelling, alongside a foundational grasp of data science techniques and workflows. We are looking for an enthusiastic learner with exceptional problem-solving skills, eager to tackle intricate data challenges.

Position Responsibilities/Major Duties:

Design, develop, optimize, and sustain data architecture and pipelines aligned with ETL principles and business objectives.
Spearhead the assessment, integration, and deployment of cutting-edge tools and processes for analytic data engineering.
Collaborate with business analysts and solutions architects to craft technical architectures for strategic enterprise projects and initiatives.

Job Functions/Requirements:

Proficiency in Azure cloud data tools, including Data Factory, PySpark, Azure Databricks, Function Apps, AAS and API Management. Recent exposure to Microsoft Fabric will be a differentiating factor.
Development expertise in Python/Spark coding on Databricks for data processing.
Utilization of Data Modelling tools such as Erwin Data Modeler or equivalent.
Conceptual understanding of data and analytics concepts, encompassing dimensional modeling, ETL, reporting tools, data governance, data warehousing, structured and unstructured data.
Self-motivated with strong problem-solving and learning aptitudes.
Strong work ethic and ability to operate at an abstract level.
Demonstrated ability to quickly grasp and apply new technologies.

Required Experience:

5 years of hands-on experience in data engineering or architecture roles.
Exposure to Lakehouse data architecture concepts.
Exposure to ML, data science, computer vision, AI, statistics, and/or applied mathematics.
Experience with Data Modeling tools.
Knowledge of Agile development methodologies, ideally with experience in Azure DevOps.

Academic Background:

Bachelor's degree or M.Sc. degree from a Canadian institution required; preferred fields include Computer Science, MIS, or Engineering.

If you are passionate about leveraging cloud technologies and data engineering expertise to drive actionable insights, we encourage you to apply for this exciting opportunity to contribute to our dynamic team.

Please include a brief introduction letter stating why you believe you would be a good fit for this position as well as what you consider to be your most important professional achievement so far.

SapienX Inc.

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