Senior Data Engineer


About the Company



We are seeking a skilled Senior Data Engineer with expertise in cloud-native data pipeline development within Microsoft environments. The ideal candidate will have a strong background in data architecture, data modelling, and the ability to implement high-performance data solutions that support our business objectives. You will play a key role in driving data-driven decision-making and enabling scalable analytics solutions across the organization.



About the Role



Required Qualifications to be successful for the senior role:



Responsibilities



  • Strong experience in end-to-end data architecture and design, including ingestion, modeling, storage, and orchestration (ex. Medallion).
  • Proficiency in cloud-native engineering, with a focus on Microsoft technologies (Fabric, Azure Data Factory, Synapse) but open to other cloud platforms (AWS, Google Cloud) with comparable tools.
  • Hands-on experience with data warehousing and data lake solutions (e.g., BigQuery, Azure Data Lake, Delta Lake, Amazon Redshift).
  • Proficiency in programming languages such as Python (with data-related libraries: e.g. Pandas, Boto3), SQL, or Spark.
  • Strong knowledge of RDBMS (e.g., Oracle, MS SQL Server) or NoSQL databases (e.g., MongoDB, ElasticSearch, GBQ).
  • Experience with DevOps/DataOps practices, including CI/CD pipelines.
  • Ability to implement data validation, lineage, documentation, and monitoring at scale.
  • Proven ability to optimize pipelines and storage solutions for performance, cost, and reliability.



Qualifications



  • Minimum 5 years of experience in data engineering, with a focus on cloud-native solutions and data architecture.
  • English proficiency should be at least B2 level.



Required Skills



  • Ability to evaluate trade-offs and make clear, defensible technical choices.
  • Translate complex engineering decisions into clear, accurate explanations for non-technical stakeholders.
  • Uplift and mentor mid/junior engineers, enforce standards, and foster a collaborative technical culture.
  • Break down ambiguous, complex problems into clear, actionable steps and drive them to resolution.
  • Take responsibility for outcomes, anticipate issues, and drive long-term platform evolution.




See also

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