Job
Description
**Role Overview:** As a Data Analytics Engineer / BI Engineer (SDE II) at Auriga IT, you will play a proactive and problem-solving role with 35 years of experience in owning end-to-end data pipelines. Your main responsibility will be partnering with stakeholders from various departments like engineering, product, marketing, and finance to convert raw data into actionable insights that steer business decisions. This position requires a blend of analytics engineering, business intelligence, and advanced data analysis, emphasizing pipeline ownership, effective stakeholder communication, and scalable analytics practices. **Key Responsibilities:** - **Pipeline Management:** - Design, build, and maintain robust ETL / ELT pipelines. - Implement orchestration workflows using tools like Airflow, dbt, or equivalent frameworks. - Own the complete lifecycle of data pipelines, including monitoring, failure handling, performance optimization, and documentation. - **Exploratory Data Analysis & Visualization:** - Conduct EDA and statistical analysis using Python or R. - Identify trends, patterns, and anomalies in extensive datasets. - Prototype and deliver interactive charts, visualizations, and exploratory dashboards. - **BI & Reporting:** - Develop and sustain dashboards and scheduled reports to highlight key KPIs and business metrics. - Facilitate self-service analytics for business users. - Configure alerts and anomaly detection for critical thresholds and data quality issues. - **Insights Delivery & Storytelling:** - Translate complex analyses (A/B testing, cohort analysis, forecasting) into actionable insights. - Present findings effectively to both technical and non-technical stakeholders. - Influence product and business decisions using data-backed recommendations. - **Collaboration, Quality & Governance:** - Collaborate cross-functionally with engineering, product, finance, and marketing teams to define data requirements. - Ensure data quality, consistency, and governance standards are adhered to. - Mentor junior analysts and engineers on clean code practices, version control, and documentation standards. - **Large Language Models (LLMs) & Applied AI:** - Demonstrate practical understanding of Large Language Models (LLMs) and their application in analytics and BI workflows. - Utilize LLMs for SQL generation, data exploration, and analytical reasoning. - Apply sound judgment on leveraging LLMs versus deterministic logic and be aware of their limitations. - **AI-Assisted Coding & Modern Code Editors:** - Comfortably work with AI-powered coding editors for writing, refactoring code, debugging pipelines, and rapid prototyping. - Maintain high engineering standards by reviewing AI-generated code, following version control processes, and ensuring auditable logic. **Qualifications:** - Bachelors or Masters degree in a quantitative field (Statistics, Computer Science, Economics, Mathematics, or similar). - 35 years of experience in a data analyst, analytics engineer, or BI engineering role. - Strong problem-solving ability, excellent communication skills, and certifications in Power BI or Tableau are advantageous. **About Auriga IT:** Auriga IT is a digital solutions company committed to creating impactful products, platforms, and data-driven experiences for global clients. The company values collaboration, long-term relationships, and a culture that combines technical excellence with a close-knit team environment, making it an ideal place for professionals interested in analytics engineering, BI, and emerging AI-driven workflows. **Role Overview:** As a Data Analytics Engineer / BI Engineer (SDE II) at Auriga IT, you will play a proactive and problem-solving role with 35 years of experience in owning end-to-end data pipelines. Your main responsibility will be partnering with stakeholders from various departments like engineering, product, marketing, and finance to convert raw data into actionable insights that steer business decisions. This position requires a blend of analytics engineering, business intelligence, and advanced data analysis, emphasizing pipeline ownership, effective stakeholder communication, and scalable analytics practices. **Key Responsibilities:** - **Pipeline Management:** - Design, build, and maintain robust ETL / ELT pipelines. - Implement orchestration workflows using tools like Airflow, dbt, or equivalent frameworks. - Own the complete lifecycle of data pipelines, including monitoring, failure handling, performance optimization, and documentation. - **Exploratory Data Analysis & Visualization:** - Conduct EDA and statistical analysis using Python or R. - Identify trends, patterns, and anomalies in extensive datasets. - Prototype and deliver interactive charts, visualizations, and exploratory dashboards. - **BI & Reporting:** - Develop and sustain dashboards and scheduled reports to highlight key KPIs and business metrics. - F
