Data Engineer

How you will contribute

You will:

• Execute the business analytics agenda in conjunction with analytics team leaders
• Work with best-in-class external partners who leverage analytics tools and processes
• Use models/algorithms to uncover signals/patterns and trends to drive long-term business performance
• Execute the business analytics agenda using a methodical approach that conveys to stakeholders what business analytics will deliver

What you will bring

A desire to drive your future and accelerate your career and the following experience and knowledge:

• Using data analysis to make recommendations to analytic leaders
• Understanding in best-in-class analytics practices
• Knowledge of Indicators (KPIs) and scorecards
• Knowledge of BI tools like Tableau, Excel, Alteryx, R, Python, etc. is a plus

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In This Role

As a DaaS Data Engineer, you will have the opportunity to design and build scalable, secure, and cost-effective cloud-based data solutions. You will develop and maintain data pipelines to extract, transform, and load data into data warehouses or data lakes, ensuring data quality and validation processes to maintain data accuracy and integrity. You will ensure efficient data storage and retrieval for optimal performance, and collaborate closely with data teams, product owners, and other stakeholders to stay updated with the latest cloud technologies and best practices .

Role & Responsibilities:

• Design and Build: Develop and implement scalable, secure, and cost-effective cloud-based data solutions.
• Manage Data Pipelines: Develop and maintain data pipelines to extract, transform, and load data into data warehouses or data lakes.
• Ensure Data Quality: Implement data quality and validation processes to ensure data accuracy and integrity.
• Optimize Data Storage: Ensure efficient data storage and retrieval for optimal performance.
• Collaborate and Innovate: Work closely with data teams, product owners, and stay updated with the latest cloud technologies and best practices.

Technical Requirements:

• Programming: Python
• Database: SQL, PL/SQL , Postgres SQL, Bigquery , Stored Procedure / Routines.
• ETL & Integration: AecorSoft , Talend, DBT, Databricks (Optional), Fivetran .
• Data Warehousing: SCD, Schema Types, Data Mart.
• Visualization: PowerBI (Optional), Tableau (Optional), Looker.
• GCP Cloud Services: Big Query, GCS.
• Supply Chain: IMS + Shipment functional knowledge good to have .
• Supporting Technologies: Erwin, Collibra, Data Governance, Airflow.

Soft Skills:

• Problem-Solving: The ability to identify and solve complex data-related challenges.
• Communication: Effective communication skills to collaborate with Product Owners, analysts, and stakeholders.
• Analytical Thinking: The capacity to analyze data and draw meaningful insights.
• Attention to Detail: Meticulousness in data preparation and pipeline development.
• Adaptability: The ability to stay updated with emerging technologies and trends in the data engineering field .