About the role
You will work closely with other analytics engineers and business stakeholders to transform raw data into trusted, analytics-ready datasets. This role is ideal for someone who is deeply technical, has strong business acumen, and is passionate about data quality, modeling best practices, and analytics enablement.
Key Responsibilities:
- Design, develop, and maintain analytics-ready datasets using modern data stack tools
- Transform raw data into clean, well-documented, and reliable datasets for analytics and BI use cases
- Develop state of the art, interactive dashboards
- Own the analytics layer of the data warehouse, ensuring consistency, accuracy, and performance
- Partner with analytics engineers to define upstream data requirements and improve data ingestion pipelines
- Collaborate with analysts and business stakeholders to translate business needs into scalable data models
- Oversee data quality checks, testing, and monitoring of the existing pipelines
- Optimize queries and models for performance and cost efficiency
Requirements:
- 3+ years of experience in analytics engineering, data engineering, or advanced analytics roles
- Strong proficiency in SQL
- Hands-on experience with modern data transformation tools (e.g., Dbt or similar)
- Hands-on experience with Azure Data Factory (ADF) for orchestration and pipeline development
- Strong experience with Azure Databricks (PySpark, Delta Lake, SQL) for data transformation
- Experience working with Azure Synapse Analytics or similar cloud data warehouse platforms
- Experience working with cloud data warehouses such as Snowflake, BigQuery, Redshift, or Databricks
- Experience working with BI tools such as Domo, PowerBI, Tableau, or Looker
- Strong understanding of data warehousing concepts, ETL/ELT pipelines, and analytics best practices
- Experience supporting BI and analytics tools
- Ability to translate complex business problems into scalable data solutions
- Strong communication skills and ability to work cross-functionally