Description

WHAT YOU'LL DO: Design, build, and optimize data pipelines and structures that support reliable, efficient data processing & delivery at scale Contribute to a growing semantic & analytics layer, including dimensional modeling for Care & Retail reporting Migrate and modernize pipelines to standardized, reusable ingestion patterns and layered data architecture Engage business teams to understand their problem space and coordinate technical changes end-to-end Perform impact analysis, diagnose issues, and validate that changes deliver expected outcomes Conduct root cause analysis on data and process issues, and flex into ad hoc analysis when the business needs answers fast Identify opportunities to consolidate redundant data objects, reduce support burden, and improve reusability Adopt and apply AI tools and modern engineering practices to improve throughput and reduce per-unit delivery overhead

 WHAT WE'RE LOOKING FOR: Experience 2-4 years of data engineering experience Experience designing & building data pipelines and data lakes in a cloud environment Experience with root cause analysis on data and process issues, with the ability to trace problems across systems and translate findings into action Comfortable flexing into an analytical or systems analyst role when the work requires it - this team supports the business, not just the pipeline Experience managing stakeholder expectations across technical & business teams Technical Skills Strong SQL, including performance tuning & optimization in large-scale analytical environments (Required) Familiarity with Microsoft Fabric, Databricks, and the Azure data stack, including Azure Data Lake Storage (Preferred) Familiarity with dimensional modeling, star schema design, and semantic layer concepts (Preferred) Familiarity with medallion architecture (bronze/silver/gold) and data lake design patterns (Preferred) Familiarity with Power BI for understanding downstream analytics consumption; DAX experience a plus (Preferred) Familiarity with Python, Scala, or other scripting languages used in pipeline development (Preferred) Familiarity with common software design principles such as DRY, SRP, and OOP (Preferred) Experience using AI tools, agents, or automation to accelerate engineering workflows (Preferred) How You Work Systems thinker: you consider how data, tools, processes, and stakeholders interact across a broader ecosystem Product owner mindset: end-to-end accountability for what you build, not just the ticket in front of you Clear communicator: you can explain technical tradeoffs to non-technical partners without losing the substance Bias toward simplicity: you ask whether complexity is necessary before adding it EDUCATION Bachelor's degree plus 2+ years of related work experience, or a combination of education & experience deemed equivalent Relevant fields include Computer Science, Statistics, Informatics, Information Systems, or a quantitative equivalent

Key Skills

Education

Any Graduate