About The Role

As a Data Engineer BI Analytics & DWH, you will contribute to building scalable data infrastructure and efficient data pipelines that power our business intelligence and analytics capabilities.

With 6 to 9 years of experience, you will apply your solid foundation in ETL/ELT development, data modelling, and database design to support data warehousing and data lake initiatives.

You will also assist in enabling data visualization through tools like Tableau or Power BI.

What You'll Do

ETL/ELT Development :

Design, build, and maintain efficient ETL and ELT processes using tools such as Azure data factory, Databricks, or similar orchestration frameworks.
Ensure reliable data ingestion from various sources into centralized storage systems (DWH/data lakes).

Data Modelling & Warehousing

Design relational and dimensional data schemas tailored to business use cases in data lakes or traditional data warehouses (e.g., Snowflake, Redshift, Postgres).
Develop and maintain data models optimized for analytics and reporting.

Database Engineering

Write efficient SQL queries and stored procedures to transform, clean, and aggregate data.
Manage data transformations and complex joins to support analytical workloads.

BI & Visualization Support

Provide basic support for report and dashboard development in visualization tools such as Tableau or Power BI.
Collaborate with analysts and business users to understand reporting needs and enable self-service BI.

Performance & Data Quality

Monitor and troubleshoot data pipelines and warehouse jobs to ensure timely and accurate data availability.
Apply basic data quality checks and validations to ensure trustworthiness of data outputs.

On your first day, we'll expect you to have :

Bachelors degree in Computer Science, Information Systems, Data Engineering, or a related field.
6 to 9 years of experience in data engineering with hands-on ETL/ELT development and data modelling.
Solid SQL skills and experience with database systems such as SQL Server, Postgres, Snowflake, or Redshift.
Exposure to cloud-based services and data tools (e.g., AWS S3, Azure Data Factory, Databricks, Lambda functions).
Basic understanding of data serialization formats like JSON, Parquet, or CSV.
Familiarity with Python for scripting and data manipulation.
Bonus : Exposure to visualization tools such as Power BI, Tableau for dashboard/report creation will be a plus.

(ref:hirist.tech)

Interesting Job Opportunity: Calfus Inc - Senior Data Engineer - ETL/Data Warehousing