Job Summary:
We are seeking a skilled Data Engineer with strong Business Intelligence (BI) development experience to design, build, and maintain scalable data infrastructure and analytics solutions. The ideal candidate will bridge the gap between data engineering and business analytics — ensuring data is clean, reliable, and easily accessible through well-designed data models, dashboards, and reports that drive strategic decision-making.
Key Responsibilities:
Data Engineering:
- Design, build, and maintain ETL/ELT pipelines for ingesting, transforming, and integrating data from multiple sources (APIs, databases, cloud services, etc.).
- Develop and optimize data warehouses, data lakes, and data marts using modern cloud platforms (AWS, Azure, GCP, or Snowflake).
- Implement data quality, data validation, and data governance best practices.
- Ensure efficient data storage, retrieval, and scalability to support BI and analytics workloads.
- Collaborate with data scientists, analysts, and business users to provide reliable and timely data.
Business Intelligence & Analytics:
- Design and develop interactive dashboards and reports using tools such as Power BI, Tableau, or Looker.
- Translate business requirements into data models, KPIs, and actionable visualizations.
- Work with stakeholders to define and document data metrics, hierarchies, and business logic.
- Optimize BI solutions for performance, scalability, and usability.
- Provide self-service BI capabilities and train users on BI tools and best practices.
Collaboration & Strategy:
- Partner with cross-functional teams (Product, Finance, Operations, Marketing) to deliver data-driven insights.
- Support the evolution of the organization’s data architecture and analytics roadmap.
- Document data workflows, technical specifications, and architecture diagrams.
Required Qualifications:
- Bachelor’s degree in Computer Science, Information Systems, Data Engineering, or a related field.
- 3–7 years of experience in data engineering and/or BI development.
- Proficiency in SQL and experience with relational and non-relational databases (e.g., PostgreSQL, MySQL, MongoDB, etc.).
- Hands-on experience with ETL tools (e.g., Airflow, dbt, Talend, SSIS, Azure Data Factory).
- Experience with cloud data platforms (e.g., Snowflake, BigQuery, Redshift, Synapse).
- Strong knowledge of data modeling (star/snowflake schemas, dimensional modeling).
- Expertise in at least one BI tool (Power BI, Tableau, Looker).
- Familiarity with Python or Scala for data transformation and automation.
- Understanding of CI/CD, version control (Git), and modern data architecture principles.