Data Engineer

Data & Analytics Engineer (BI + Data Integration)

Summary

We are looking for a Data & Analytics Engineer to design, build, and maintain the data pipelines, data models, and BI reporting layer that power enterprise dashboards and operational analytics. This role sits at the intersection of data engineering, business intelligence, and analytics, supporting both strategic reporting and system-to-system data integration.

You will work closely with business stakeholders, data analysts, and engineering teams to ensure reliable, well-structured, and high-quality data is available for reporting and decision-making across the organization.

This role is ideal for someone who enjoys both building data pipelines and delivering actionable insights through BI tools and dashboards.

Key Responsibilities

Data Integration & Pipelines

• Design, build, and maintain ETL/ELT pipelines that integrate data from multiple internal and external systems
• Work with APIs, web services (REST/SOAP), and flat-file integrations to support data movement and synchronization
• Define and implement data mapping between source systems and analytical models
• Monitor, troubleshoot, and optimize data pipelines to ensure reliability and performance
• Partner with engineering and business teams to resolve data quality and integration issues

Data Warehousing & Modeling

• Develop and maintain scalable data warehouse models to support reporting and analytics
• Design and implement fact and dimension tables, data marts, and reusable datasets
• Ensure data consistency, integrity, and alignment across reporting systems
• Translate business requirements into structured data models optimized for BI consumption

Business Intelligence & Reporting

• Build, enhance, and maintain dashboards and KPI reports using BI tools such as: Tableau and/or Microsoft Power BI
• Collaborate with business stakeholders to define reporting requirements and success metrics
• Ensure dashboards are accurate, performant, and aligned with enterprise definitions
• Support self-service analytics by enabling well-structured and documented datasets

Collaboration & Stakeholder Engagement

• Work closely with business users to translate reporting needs into technical solutions
• Partner with analysts, engineers, and product teams across the data lifecycle
• Communicate technical concepts clearly to non-technical stakeholders
• Participate in Agile development cycles and sprint planning

Required Skills & Experience

• 2–5 years of experience in data analytics, BI development, or data engineering
• Strong SQL skills (query optimization, joins, aggregations, window functions)
• Experience working with data warehouses (e.g., Snowflake, Teradata, BigQuery, or similar)
• Experience building or supporting ETL/ELT pipelines
• Hands-on experience with at least one BI tool (Tableau, Power BI, MicroStrategy, etc.)
• Understanding of data modeling concepts (star schema, fact/dimension design)
• Experience working with APIs or structured data integrations (JSON/XML preferred)
• Strong analytical and problem-solving skills
• Excellent communication skills and ability to work with business stakeholders

Preferred Qualifications

• Experience with enterprise reporting environments or KPI standardization
• Familiarity with cloud data platforms (AWS, Azure, or GCP)
• Experience with workflow orchestration tools (Airflow, dbt, or similar)
• Exposure to healthcare, finance, or other regulated data environments
• Experience documenting data definitions and governance standards

What Success Looks Like

• Business users trust dashboards and metrics as a single source of truth
• Data pipelines are reliable, monitored, and easy to maintain
• Data models are reusable and scalable across reporting needs
• Integration issues are quickly identified and resolved
• Reporting requests are delivered efficiently with minimal rework

Why This Role Is Exciting

This role gives you ownership across the full analytics stack—from raw data integration to polished dashboards. You’ll directly influence how data is structured, understood, and used across the organization, while working in a collaborative and fast-moving environment.