Summary

We are seeking a skilled Data Engineer to design, build, and maintain robust data pipelines and analytics infrastructure. The ideal candidate will have strong hands-on experience in ETL development,Azure Databricks, and Power BI integration, enabling efficient data flow and insight generation across the business.

This role will work closely with analysts, data scientists, and business stakeholders to ensure data is clean, reliable, and readily available for decision-making.

Key Responsibilities

Design, develop, and maintain ETL pipelines for data ingestion, transformation, and loading across multiple data sources.
Build and optimize data workflows and models using Azure Databricks and PySpark/SparkSQL.
Develop and maintain data models supporting analytics and reporting in Power BI.
Implement data quality, validation, and monitoring frameworks to ensure reliability and integrity.
Collaborate with business teams to understand reporting requirements and translate them into scalable data solutions.
Support data warehousing and data lake solutions within Azure ecosystem (Data Lake Storage, Synapse, etc.).
Maintain and enhance metadata, data lineage, and documentation for all data processes.
Optimize performance of queries and pipelines for scalability and cost efficiency.
Ensure security, compliance, and access control within all data environments.

Additionally, you'll also be comfortable in working on application development projects for our client who is a reputable business operating within the Alcohol, Tobacco, and Sanitary industry sector

Qualifications

Skill and experiences

Min. 4+ years of experience in data engineering. Strong hands-on experience with the following:
ETL tools and frameworks (e.g., Azure Data Factory, SSIS, or custom Python pipelines)
Databricks (PySpark, SparkSQL, Delta Lake, cluster management)
SQL and relational database design (e.g., SQL Server, Snowflake, or Azure Synapse).
Power BI (data modelling, DAX, dataset management, dashboard integration).
Familiarity with Azure ecosystem (Data Lake, Synapse Analytics, Key Vault, Logic Apps).
Solid understanding of data modelling, data governance, and best practices for performance tuning.
Strong analytical thinking, problem-solving, and communication skills.

Azure Data Engineer (ADF)