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Manager of Data Engineering and Functional Consulting

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Manager of Data Engineering and Functional Consulting

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  • Bachelor's or Master's degree in Computer Science, Information Systems, Data Analytics, or a related field.
  • Strong understanding of end-to-end data warehousing concepts, including data modeling, ETL/ELT, and data integration.
  • Proficient in Azure Synapse, Databricks, Azure Data Factory, Snowflake, and Power BI for modern cloud-based data solutions.
  • Skilled in handling structured, semi-structured (JSON, XML), and unstructured data across Azure and AWS platforms.
  • Expertise in Power Query and Power M for advanced data transformation and reporting automation.
  • Solid grasp of Agile methodologies, functional requirement gathering, and stakeholder communication.
  • Familiar with metadata management, data lineage, and data quality principles to ensure trusted analytics.

Experience

  • 10+ years of experience in designing, implementing, and optimizing end-to-end data warehouse solutions across cloud and on-premise ecosystems.
  • Orchestrated enterprise DWH solutions using Azure Synapse, Databricks, and ADF, integrating structured and semi-structured data sources while ensuring lineage, auditability, and performance at scale.
  • Translated business needs into scalable dimensional models and Power BI solutions, leveraging Power Query (M) scripting and DAX for self-service analytics.
  • Designed and governed hybrid data pipelines across Azure and AWS, ensuring data consistency, compliance, and traceability from ingestion to visualization.
  • Collaborated with stakeholders and engineering teams to define KPIs, automate reconciliations, and embed validation rules across ETL and reporting layers.
  • Led multi-cloud integration of systems into a unified analytics layer, optimizing transformations with Databricks notebooks, ADF workflows, and parameterized datasets.
  • Enabled real-time insights by architecting incremental refresh in Power BI and optimizing semantic models with measures, security, and models.
  • Implemented data observability frameworks to proactively detect anomalies and ensure SLA adherence across reporting layers.
Seniority level
  • Not Applicable
Employment type
  • Contract
Job function
  • Engineering and Information Technology
Industries
  • IT Services and IT Consulting

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