Data Engineer

• Build & Maintain Data Systems: Develop and manage robust, scalable data warehouses, databases, and pipelines.

• ETL/ELT Processes: Create and optimize processes to extract, transform, and load data from diverse sources.

• Data Quality & Integrity: Implement checks, clean data, and ensure accuracy and reliability for analytics.

• Collaboration: Work with data scientists, analysts, and product teams to meet data needs.

• Infrastructure: Design data architecture for efficient storage, retrieval, and processing.

• Automation & Optimization: Automate manual tasks and optimize performance of data systems.

• Security & Compliance: Implement security measures and ensure data privacy.

• Dashboard Creation / Update: Work with BI tools to create and optimize dashboards and reports for business users

Requirements

• Education: Degree in Computer Science or related field.

• BI tools such as Power BI & Tableau : Complex DAX, Visualization, Dashboard Performance tuning

• Databases: SQL, NoSQL, database design, data modelling.

• Tools: ETL tools, data warehousing solutions, API integrations.

•Programming: Python, Java, SQL (strong expertise).

• Soft Skills: Analytical skills, problem-solving, communication, teamwork.

•Business Acumen: Deep understanding of business processes, pain points, and strategic goals to proactively identify data and reporting needs.

• Big Data: Familiarity with tools like Spark, Hadoop, Kafka, Hive.

• Cloud: Experience with cloud platforms (AWS, Azure, GCP) is often required.

• Excel Mastery: Utilize advanced features in Microsoft Excel (PivotTables, advanced formulas, data modelling) for ad-hoc analysis, prototyping, and data validation.