About the Role

insightsoftware is looking for a data professional who brings strong technical fundamentals, a genuine curiosity for AI, and the ability to translate business needs into data solutions. As a Data Engineer on the Enterprise Data team, you will design and maintain scalable data pipelines, build Power BI solutions that drive decisions, and champion AI-assisted workflows that make the team faster and smarter. This role sits at the intersection of engineering precision and business partnership .

What You Will Do

Data Engineering

• Design, build, and maintain ELT/ETL pipelines that move data reliably from source systems into a cloud data warehouse environment.

• Write clean, performant, and well-documented SQL to transform raw data into analyst-ready models and reporting layers.

• Partner with the team to define and enforce data modeling standards, naming conventions, and documentation practices.

• Monitor pipeline health, troubleshoot failures, and implement proactive alerting to protect data availability.

Business Intelligence & Reporting

• Develop and maintain Power BI dashboards and reports that give business stakeholders clear, trusted views of company performance.

• Apply best practices in data modeling within Power BI (star schemas, DAX measures, performance optimization) to ensure reports are fast and maintainable.

• Work closely with business partners to understand reporting requirements, translating ambiguous asks into structured analytical deliverables.

• Champion self-serve analytics by building reusable semantic layers that reduce ad hoc request volume.

AI-First Ways of Working

• Actively use AI tools (such as LLM assistants, copilots, and agentic workflows) to accelerate development, improve code quality, and generate documentation.

• Identify opportunities to apply AI and automation to repetitive data tasks, from data quality checks to pipeline scaffolding.

• Stay current on emerging AI/data tooling and share practical learnings with the team.

• Apply a critical, evidence-based lens to AI outputs, validating results before using them in production.
  

Business Partnership

• Engage directly with business stakeholders to understand data needs in context, asking smart questions and pushing back constructively when requirements are unclear.

• Communicate technical concepts and data limitations in plain language, building trust with non-technical partners.

• Contribute to data governance practices, including metadata documentation, lineage tracking, and data quality standards.

What You Bring

Required

• 3+ years of hands-on data engineering or analytics engineering experience in a professional setting.

• Strong SQL skills: complex joins, window functions, query optimization, and data modeling.

• Demonstrated Power BI proficiency , including report development, data modeling, and DAX.

• Experience working with cloud data warehouse platforms (Snowflake, BigQuery , Redshift, or similar).

• Proven, active use of AI tools in daily data work, not just awareness.

• Ability to engage with business stakeholders and translate requirements into data solutions.

• Strong written and verbal communication skills .

Preferred

• Experience with ELT/ETL orchestration tools such as Fivetran , dbt , or similar.

• Familiarity with Salesforce data structures or CRM-adjacent reporting.

• Exposure to agentic AI workflows, prompt engineering, or LLM-powered automation.

• Background in financial or ARR/revenue data domains.

• Experience with role-based access control and data security practices in cloud platforms.