JOB DESCRIPTION:

We are seeking a meticulous and skilled Data Engineer / Analyst to join our dynamic team. The ideal candidate will be responsible for designing and developing scalable data pipelines, building and maintaining a centralized data warehouse, and ensuring the accuracy and integrity of both automated and manual data reports.

REQUIREMENTS:

• Bachelor’s degree in Computer Science, Data Science, Engineering, or related field.
• 2+ years of hands-on experience in data engineering or analytics roles.
• Proficiency in SQL, Python, and data modeling techniques.
• Hands-on experience with Databricks, Snowflake, or Microsoft Fabric (at least one is mandatory; familiarity with others is a plus).
• Strong understanding of data warehouse architecture and ETL/ELT processes.
• Experience working with APIs, cloud storage, and data lake architectures.
• Familiarity with orchestration tools such as Airflow, DBT, Azure Data Factory, or similar.
• Experience in building dashboards using Power BI, Tableau, or equivalent.
• Knowledge of data quality frameworks and data observability tools is a plus.

PREFERRED QUALIFICATIONS:

• Experience in a similar role within a fast-paced environment.
• Knowledge of additional programming languages (e.g., Python, R).
• Understanding of database management, data warehousing, and data lakes.
• Familiarity with reporting tools (e.g., Tableau, Power BI, Looker).
• Exposure to healthcare or regulated environments is an advantage.

• Validate and ensure the accuracy of automated and manual data reports.
• Architect and implement robust data warehouse solutions.
• Use pandas and other data analysis tools to clean and process data.
• Handle change requests for existing automated reports.
• Collaborate with the team to automate new reports based on client requirements.
• Develop and maintain dashboards for data visualization using tools like Tableau, Power BI, or similar.
• Create and manage data pipelines for automated streaming of data into clients’ data lakes.
• Ensure consistency and reliability of data sources for manual reports.
• Conduct regular data audits to maintain data integrity.