Data Engineer

The Data Engineer will collaborate with cross-functional teams to understand data requirements, design, develop, and implement efficient data pipelines, and ensure the availability, reliability, and scalability of our data solutions. The position is instrumental to the implementation of our enterprise data strategy, which involves designing, developing, and maintaining our data infrastructure and systems. This position necessitates proficiency in data manipulation, data analysis, relational databases and query development, data modeling, and the orchestration of ETL (Extract, Transform, Load) processes.

List the essential functions (i.e. key responsibilities with expected end results) that must be accomplished in order to fulfill the purpose of your position as described above.

Discover the information hidden in vast amounts of data. Help to make smarter decisions to business by delivering a single source for truth for data. Primary focus would be in applying advance analytics methods and techniques to provide insights and actionable recommendations.
Develop and maintain a large-scale data environment consisting of wide-ranging functional data: finance, operations, sales, marketing, quality, etc.
Gather and integrate data from various sources and proficiently design and develop SQL queries to retrieve and analyze data stored in multiple databases.
Implement and maintain data quality and data governance processes, including data cleansing, validation, and metadata management.
Develop ETL processes to clean, transform, and enrich data in PowerQuery, ensuring data quality, consistency, and accuracy for use in the PowerBIs Data model
Design and develop data model, transform raw data into meaningful insights, create relationships, hierarchies, and calculated measures in PowerBI s Data Model
Optimize data models, database schemas, and data processing algorithms to ensure efficient and high-performance data storage and retrieval.
Monitor and troubleshoot data pipelines, identifying and resolving performance or data quality issues in a timely manner.
Document data integration and transformation processes for future reference and troubleshooting.
Develop and implement data security and privacy measures to ensure compliance with regulations and industry best practices.
Implement row-level security (RLS) and object-level security (OLS) in Power BI to restrict data access based on user roles and criteria.
Collaborate with infrastructure and operations teams to ensure the availability, reliability, and scalability of data systems and infrastructure.
Mentor and provide technical guidance to the team, promoting best practices and knowledge sharing.
Experience with agile development methodologies and version control systems is preferred.

Minimum Graduate in Mathematics, Business, Economics.
3-5 years of experience - manufacturing industry exposure preferred.

Microsoft Power BI experience mandatory (PowerQuery, Modelling, DAX, Relationship & Security)
SQL query language mandatory
Data Engineering basic - (Extracting (relevant data), transforming (cleaning data), and loading (calculating & integrating) data from multiple sources to a single repository.) - Mandatory
Using data and managing from RDBMS/ databases. Metadata, Taxonomies
Strong analytical skills- prior experience of working on big data analytics projects - Preferred
Prior experience of establishing a well-managed enterprise environment in MS Azure- Preferred
Hands-on experience in Project Management tools like Jira - preferred.
Analytical modeling experience - Mandatory
Strong business acumen (of whichever industry the candidate belongs)
Alteryx and Alation hands-on desirable.

Ability to multi-task and be proactive & independent in a dynamic environment.
Highly motivated individual with excellent oral and written communication skills.
Strategic and Critical approach towards solving problems and decision making
Results-oriented; proven ability to prioritize, drive and achieve results
Excellent communication skills - storytelling, concept pitching.