Data engineer

SCOPE:
The Data Engineer will work with IT and Advanced Analytics to bridge the gap between raw data infrastructure and business intelligence, build reliable pipelines, curated data models, and scalable reporting solutions.
Qualifications:
Bachelor's degree in a relevant field (e.g., Statistics, Mathematics, Computer Science, Business) or equivalent practical experience.
Proven experience as a Data Engineer with a minimum of 2-3 years in a similar role.
Proficiency in data engineering tools such as SQL, Python, R, or other relevant languages.
Experience with data visualization tool (Power B).
Strong analytical and problem-solving skills with a keen attention to detail.
Excellent communication skills to convey complex data findings to non-technical stakeholders.
Self-motivated with the ability to work both independently and collaboratively in a fast-paced environment.
SKILLS:
Skills Required: Python, My SQL, Py Spark, No SQL, SQL Server, Windows, Linux(Shell, API, Batch scripting), GIT, Documentation, Azure, Data Warehousing, Snowflake
Good to have: Postgre SQL, Full Stack Web Dev, UNIX, API Development, Automation Development, MS Office tools development, PBI/Tableau/Google Analytics, Dev Ops Automation, Fivetran
DUTIES AND RESPONSIBILITIES:
Build and maintain data pipelines between source data and analytical databases.
Implement and evangelize engineering best practices for sustainable and scalable delivery.
Work with solution architect, Data Modelers, BI Analysts and Product Managers to take an active role in solution design.
Help identify MVP and iterative design approach in an agile framework.
Identify necessary business rules for extracting data along with functional and technical risks related to data sources.
Develop initial Queries for profiling data, validating analysis, testing assumptions, driving data quality assessment specifications, and define path to deployment.