Data Engineer

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    "description": "<p><span style=\"color: rgb(230, 126, 35); font-size: 18pt; font-weight: bold\"><span style=\"font-weight: bold\">Company Overview</span></span></p>\n<p><span style=\"font-size: 12pt; font-weight: bold\"> Job Overview</span></p>\n<p><span style=\"font-family: Arial; font-size: 12pt\">Startup tech company. They offer a no‑code AI workflow platform designed to help commercial real estate professionals — including brokers, landlords, and retail operators — simplify and automate routine and time‑intensive tasks. The core idea is to reduce manual busywork that slows down deal cycles and drains time. Their platform lets users: Build custom AI workflows in minutes without writing code Automate site analysis and research (e.g., evaluating location data used in property decisions) Keep deal pipelines up to date by automatically running tasks that would normally require manual input Trigger outreach or next steps based on workflow results (e.g., follow‑ups) Integrate conversational AI with visual workflow builders so teams can interact with their data naturally while the automation runs behind the scenes 24/7.</span></p>\n<p> <br><span style=\"font-size: 14pt; font-weight: bold\">Job Description</span> <br></p>\n<p>We are looking for a skilled Data Engineer to design, optimize, and maintain the data architecture that powers our BI environment. This role focuses on building scalable Big Query DataMart's, optimizing data models, and ensuring reliable data pipelines to support analytics and reporting.</p>\n<p>The ideal candidate has strong experience in cloud data warehousing, data modelling, and building analytics-ready datasets that enable efficient BI consumption.</p>\n<p><br><span style=\"font-weight: bold\">Key Responsibilities</span></p>\n<ul>\n<li>Data Architecture &amp; Engineering</li>\n<li>Design, build, and maintain Big Query DataMart's and analytical tables for BI reporting</li>\n<li>Develop scalable data models (star schema, snowflake, or denormalized) optimized for analytics workloads</li>\n<li>Optimize query performance and storage efficiency within cloud data warehouses</li>\n<li>Collaborate with BI teams to ensure datasets align with semantic models and dashboards</li>\n<li>Data Pipeline &amp; Transformation</li>\n<li>Build and maintain data pipelines for data ingestion, transformation, and loading into analytics environments</li>\n<li>Implement transformation workflows using SQL or frameworks such as dbt</li>\n<li>Ensure data quality, validation, and consistency across datasets<br></li>\n<li>Data Governance &amp; Performance</li>\n<li>Maintain data standards, naming conventions, and proper documentation</li>\n<li>Implement governance practices, including schema management and version control</li>\n<li>Monitor and troubleshoot pipeline failures and data inconsistencies</li>\n<li>Work closely with BI specialists to ensure datasets support semantic layer requirements</li>\n<li>Deliver optimized datasets that minimize the need for heavy transformations within BI tools</li>\n</ul>\n<p><br></p>\n<p><span style=\"font-size: 12pt; font-weight: bold\">Required Qualifications</span></p>\n<ul>\n<li>3+ years of experience in Data Engineering or Analytics Engineering</li>\n<li>Strong SQL expertise for analytical workloads</li>\n<li>Experience with cloud data warehouses (Big Query, Redshift, Snowflake, or similar)</li>\n<li>Proven experience in designing star schema or dimensional data models</li>\n<li>Experience building analytics-ready Datamart's<br>   </li>\n<li><span style=\"font-weight: bold\">Preferred Qualifications</span></li>\n<li>Experience with dbt or similar data transformation frameworks</li>\n<li>Experience working with BI tools such as Looker, Tableau, or Power BI<br></li>\n<li>Background in retail or multi-location data environments</li>\n<li>Familiarity with Git-based workflows and CI/CD for data pipelines<br><br><br><span style=\"font-weight: bold\">Skills: </span><br>Prompt Engineering, SQL</li>\n</ul>\n<p><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br></p>\n<p><span style=\"color: rgb(230, 126, 35); font-size: 18pt; font-weight: bold\"><br><br></span></p>",
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