ROLES AND RESPONSIBILITIES:
✅ Understand, design, develop, and expand data engineering technical stacks: ETLs,
Data Stores, Data Warehouses, 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 is 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, and 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 build 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.
✅ Work with architects contributing to the data and analytics team on best practices in backend infrastructure, cloud transformation, and distributed computing topics.
✅ Manage the monitoring of all data cleansing/quality activities including support and guidance to business users to support all reporting needs, and data profiles.
✅ Develop team’s data capabilities with knowledge sharing, enforcing best practices, and building a data-driven organization
MINIMUM JOB REQUIREMENTS:
✅ Bachelor’s Degree in Computer Science or Engineering courses
✅ Innovative, proactive, creative, well-organized, and able to easily adapt to various technologies.
✅ Great interpersonal skills and excellent oral and written communication skills. Able to manage work with internal stakeholders and vendors.
✅ Willingness and desire to learn new environments and tools and advance your knowledge. Keeps up to date with new research and integrated applications in data science.
✅ Able to work with loosely defined requirements and exercise analytical skills to clarify questions, share methodology/approach, and build/test solutions.
✅ At least 10 years of experience in designing, and building data warehouses or data lakes.
✅ Prior experience in applications analysis, design, and development
✅ Must understand how to interpret customer business needs and translate them into the application and operational requirements.
✅ Must have extensive knowledge of emerging industry practices.
✅ Microsoft Azure experience specifically Azure Data Factory, Azure SQL DB / Data Lake, and/or Databricks.