Data Engineering Senior Consultant

Company Highlights:

• Hybrid Work Arrangement (Work from Home and Office)
• Regular Company Events (Sports Tournament, Outdoor Activities)
• Gym, Dental, Optical

Responsibilities:

• Lead and support client project implementations with advanced analytics, project planning, and communication, focusing on data integration and transformation using ETL/ELT processes.
• Design, develop, and optimize robust data pipelines and workflows for data warehouse, data marts and (optionally) data lakehouse environments, ensuring high performance, scalability, and data quality.
• Develop, optimize, and maintain complex SQL queries, stored procedures, and database objects for data transformation, aggregation, and reporting. Implement indexing, partitioning, and performance tuning for large-scale datasets.
• Utilize and manage ETL tools (e.g., Azure Data Factory, Microsoft SSIS, Qlik Talend, Informatica, etc.) to extract, transform, and load data from diverse sources, ensuring data integrity and consistency.
• Build and maintain advanced dashboards and reports using Microsoft Power BI, leveraging DAX, Power Query, and custom visuals to deliver actionable insights. Implement row-level security, data modeling, and interactive analytics features.
• Leverage experience with cloud data platforms such as Snowflake or Databricks for scalable data processing, real-time analytics, and integration with machine learning workloads (preferred but not required).
• Interpret and analyze data to identify trends, optimize supply chain and business processes, and provide actionable recommendations to clients.
• Collaborate with project leads, system architects, and client teams to establish data best practices, success criteria, and ensure alignment with business objectives.
• Communicate key results and insights to stakeholders in verbal, visual, and written formats, translating complex technical findings into business value.
• Support research initiatives for solution design, continuous improvement, and adoption of new data technologies.
• Willingness to learn new applications such as SAP's BI solutions

Requirements:

• 4 to 10 years of relevant experience in data analytics, data engineering, or related fields.
• Bachelor's degree in Computer Science, Information Technology, Data Science, or a related fields.
• Strong analytical, problem-solving, and communication skills, with the ability to translate business requirements into technical solutions.
• Proven expertise in data warehouse architecture design and implementation.
• Proven expertise in ETL/ELT processes development, advanced SQL (including writing, optimizing, and troubleshooting stored procedures, functions, and complex queries).
• Hands-on experience with ETL tools (e.g., Azure Data Factory, Qlik Talend, Microsoft SSIS, Informatica, etc.) and data visualization tools (Microsoft Power BI, Tableau, or similar), including advanced skills: data modeling, DAX, Power Query, dashboard/report design, and deployment.
• Strong attention to detail, documentation, and testing skills.
• Good communication and teamwork abilities; willingness to learn from senior colleagues and adapt to new tools and technologies.
• Ability to support multiple tasks, prioritize effectively, and work collaboratively within a project environment.
• Hands-on experience with cloud computing platforms such as AWS, Azure, GCP is a strong advantage.
• Familiarity with data lakehouse concepts and real-time data processing, including experience with cloud data platforms such as Snowflake or Databricks is a plus.
• CI/CD pipeline development experience is highly desirable.
• Understanding SAP systems (especially SAP HANA); experience with SAP Datasphere or SAP Analytics Cloud (SAC) is a plus.
• Experience with accounting terminology and concepts is an advantage.
• Experience coding with Python scripts language and data related library (e.g., Pandas, PyMySQL) is a plus.
• Parallel programming using PySpark is a plus.