Analytics & Data Engineer - Remote

Overview

The Analytics & Data Engineer role is engaged in architecture, consulting and development of Data Engineering and Business Intelligence solutions related to client projects. This role will also participate in activities that are directed at the overall growth of the Analytics and Data Estate Practice within Hammer Dev. This is a client facing role requiring excellent relationship management, communication, and solution architecture / development skills.

In Short

• Support solution decision-making as a trusted technical advisor.
• Design, implement, and deploy data platforms in public and private cloud environments.
• Guide clients on data strategy, governance, architecture, and quality management.
• Conduct customer workshops, discovery sessions, and presentations.
• Educate clients on modern technologies and their business value.
• Define processes and tools for data acquisition, storage, transformation, and analysis.
• Communicate solution and technology options and their business impact.
• Develop roadmaps and implementation strategies for data initiatives.
• Review and audit existing solutions and create architecture documentation.
• Discuss solutions with stakeholders from C-level to engineering teams.

Requirements

• Excellent analytical, verbal, written, and communication skills.
• Ability to communicate professionally with senior leadership in the role of project leader.
• Contribute to an engaging work environment.
• Provide technical expertise in business analytics, data integration, and visualization.
• Specialist knowledge in major relational and NoSQL-type data platforms.
• Specialist knowledge of Microsoft Fabric workloads including Reporting (Power BI interactive and Paginated Reporting), Data Engineering, Data Factory, Data Science, Data Warehouse, Database & Real-Time Intelligence.
• Expert-level skillset and experience architecting and developing all components of modern analytics stacks, including MDM, normalization, Business Intelligence / Visualization, relational data warehouse / lake house structures, popular schemas, ETL & ELT.
• Ability to identify company requirements for data insights and warehousing.
• Comfortable working with various corporate stakeholders.
• Expert in architecting Data Lakes and modern data concepts.

Benefits

• Experience with Row-Level Security.
• Experience leveraging Python and GenAI for development.
• Nice to Have: Experience with big data technologies, Data Bricks, and Snowflake.
• Experience with Kimball, Bottom-Up, Top-Down, Inmon, and Data Vault concepts.
• Experience with Star & Snowflake.
• Experience with Azure Data Factories, SSIS, Azure Synapse Analytics and Azure Stream Analytics.