Senior / Lead Data Engineer
3 semanas atrás
Required Qualifications to be successful for both roles (Senior/Lead profiles): Technical Skills: 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. Soft 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.
Experience
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.
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