01Overview
Area(s) of responsibility
Skills: Data Engineer- Data Bricks, Pyspark, SQL, Python
Exprience: 4-7 years
Position Summary
The Data Engineer need to lead the design, development, and optimization of scalable data pipelines and analytics platforms. Need to work with large and complex datasets to help the organization make informed, datadriven decisions. This role involves data collection, cleansing, analysis, development, testing, visualization, and reporting while collaborating closely with crossfunctional business and technology teams.
Key Responsibilities
- Data Preparation & Management
- Clean, prepare, and validate data for analysis
- Acquire data from primary and secondary sources; build and maintain data systems and databases.
- Identify, analyse, and interpret patterns or trends in complex datasets
- Data Analysis & Insights
- Perform exploratory and statistical data analysis to support business decisions.
- Provide insights that drive performance improvements, revenue optimization, and customer experience enhancements
- Support business case creation with datadriven analysis.
- Conduct adhoc analysis for leadership and product teams
- Data transformations.
- Build large-scale data processing solutions using Databricks (Scala, Spark SQL, PySpark, Python).
- Design, optimize, and manage Snowflake data warehouse structures and workloads.
- Ensure data quality, performance, governance, and automation across pipelines.
- Build and optimize SSAS Tabular Models and support enterprise BI solutions.
- Lead end-to-end design and delivery of ETL/ELT pipelines using SQL, SSIS, databricks jobs.
- Reporting & Visualization
- Develop high quality dashboards, reports, and visualization assets for stakeholders using power BI, data bricks dashboards.
- Translate complex datasets into explicit, concise business insights using tools such as Power BI.
- Collaboration
- Work with technology, product, and management teams to define business needs and analytical requirements.
- Co .
