Senior Data Engineer

We are seeking a highly skilled and motivated Senior Data Engineer to join our dynamic data team. In this role, you will lead the design, development, and maintenance of robust data pipelines and architectures that empower data-driven decision-making across the organization. You will leverage your expertise in big data systems, cloud platforms, and data modeling to create scalable solutions that handle vast amounts of information efficiently. This position offers an exciting opportunity to work with cutting-edge technologies in a fast-paced environment, driving innovation and delivering actionable insights through advanced data engineering practices., * Develop, optimize, and maintain large-scale ETL (Extract, Transform, Load) pipelines using tools such as Informatica, Talend, and custom Python scripts to ensure seamless data flow across diverse systems.

• Design and implement scalable data models and schemas for data warehouses utilizing dimensional modeling principles to support business intelligence and analytics initiatives.
• Build and manage cloud-based big data solutions on platforms like AWS, Azure Data Lake, and Public Cloud environments to facilitate secure and efficient data storage and processing.
• Collaborate with cross-functional teams to integrate linked data sources, ensuring consistency and accuracy across datasets.
• Develop SQL queries, stored procedures, and database designs for SQL databases such as Microsoft SQL Server, Oracle, and cloud databases to enable effective query management and reporting.
• Implement advanced analytics solutions by training models using Spark, Hadoop, Apache Hive, and other big data tools to uncover insights from complex datasets.
• Support business intelligence tools like Looker by creating dashboards and reports that translate technical data into clear visualizations for stakeholders.
• Contribute to agile development cycles by participating in sprint planning, code reviews, and continuous improvement initiatives focused on data management integration and software development best practices.

• Proven experience as a Data Engineer or in a similar role with a strong background in software development within big data environments.
• Extensive hands-on experience with cloud platforms such as AWS or Azure Data Lake for designing scalable data solutions.
• Proficiency in programming languages including Java, Python, Bash (Unix shell), Shell Scripting, and VBA for automation and pipeline development.
• Deep understanding of big data systems such as Hadoop ecosystem components (HDFS, Spark, Hive) along with ETL tools like Informatica or Talend.
• Strong knowledge of SQL databases including Microsoft SQL Server, Oracle, and cloud-based database solutions; expertise in data warehousing design and dimensional modeling techniques.
• Familiarity with RESTful APIs for integrating various systems and services within the enterprise architecture.
• Experience with business intelligence tools such as Looker or similar platforms for creating insightful dashboards.
• Excellent analysis skills combined with the ability to design efficient data models that support complex queries and reporting needs.
• Knowledge of public cloud environments (AWS, Azure) along with best practices for security, scalability, and cost management in cloud-based big data systems.