Data Engineer

About The Role

highly skilled Data Engineer

Power BI, SQL, Python

Big Data ecosystems

Key Responsibilities

• Data Modelling & Visualization
• Build scalable and high-quality data models in Power BI using best practices.
• Define relationships, hierarchies, and measures to support effective storytelling.
• Ensure dashboards meet standards in accuracy, visualization principles, and timelines.
• Data Transformation & ETL
• Perform advanced data transformation using Power Query (M Language) beyond UI-based steps.
• Design and optimize ETL pipelines using SQL, Python, and Big Data tools.
• Manage and process large-scale datasets from various sources and formats.
• Business Problem Translation
• Collaborate with cross-functional teams to translate complex business problems into scalable, data-centric solutions.
• Decompose business questions into testable hypotheses and identify relevant datasets for validation.
• Performance & Troubleshooting
• Continuously optimize performance of dashboards and pipelines for latency, reliability, and scalability.
• Troubleshoot and resolve issues related to data access, quality, security, and latency, adhering to SLAs.
• Analytical Storytelling
• Apply analytical thinking to design insightful dashboards—prioritizing clarity and usability over aesthetics.
• Develop data narratives that drive business impact.
• Solution Design
• Deliver wireframes, POCs, and final solutions aligned with business requirements and technical feasibility.
  

Required Skills & Experience

• Minimum 3+ years of experience as a Data Engineer or in a similar data-focused role.
• Strong expertise in Power BI: data modeling, DAX, Power Query (M Language), and visualization best practices.
• Hands-on with Python and SQL for data analysis, automation, and backend data transformation.
• Deep understanding of data storytelling, visual best practices, and dashboard performance tuning.
• Familiarity with DAX Studio and Tabular Editor.
• Experience in handling high-volume data in production environments.
  

Preferred (Good To Have)

• Exposure to Big Data technologies such as:
• PySpark
• Hadoop
• Hive / HDFS
• Spark Streaming (optional but preferred)
  

Why Join Us?

• Work with a team that's passionate about data innovation.
• Exposure to modern data stack and tools.
• Flat structure and collaborative culture.
• Opportunity to influence data strategy and architecture decisions.