Data Engineering Consultant

Acts as a technical lead and subject matter expert for the team on data engineering technical stack and integration tools and best practices used in analytics data management.

• Understand, design, develop, and expand data engineering technical stacks: ETLs, Data Stores, Data Warehouse, Data Lakes, Data Hubs, Data Governance, Visualization, Performance, Infrastructure, and Governance in either enterprise/ open source/ bespoke solutions or platforms.
  • Expertise in tools and solutions related to data governance which includes but not limited to analyzing and visualizing diver sources of data, discovering data sources and making them available through ETL as part of the data democratization initiative
  • Apply data mining and wrangling on data
  • Identify opportunities to optimize the ETL environment, implement monitoring, quality, and validation processes to ensure data accuracy and integrity.
  • Provide inputs in data governance to drive data governance charter
  • Implement data pipelines to bring data at reach to platforms or tools used by different business units. Maintain development roadmap aligned with product and infrastructure objectives to support advanced data solutions
  • Analyze source data and data flows and building APIs or solutions for data consumption or integration to different tools
  • Provide subject matter expertise or support to data engineering technical stack post-production
  • Design and implement solutions for integrating, streaming, processing, and storage of data. This also includes data in data warehouses, data lakes, and/or data hubs and handling of structured, semi-structured, and unstructured data
• Works with architects contributing to the Data Analytics team on best practices in backend infrastructure, cloud transformation, and distributed computing topics.
• Manages monitoring of all data cleansing/quality activities including support and guidance to business users to support all reporting needs, data profiles.
• Develops team’s data capabilities with knowledge sharing, enforcing best practices, and building a data-driven organization.

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