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 development and optimization of large-scale data systems, ensuring seamless data integration, management, and analysis across diverse platforms. Your expertise will drive innovative data solutions that empower business intelligence and strategic decision-making. This position offers an exciting opportunity to work with cutting-edge technologies in a fast-paced environment, contributing to the organization’s data-driven success., * Design, develop, and maintain scalable ETL (Extract, Transform, Load) pipelines to facilitate efficient data flow from various sources into centralized data warehouses and lakes.

• Implement and optimize big data systems using tools such as Hadoop, Spark, Apache Hive, and Azure Data Lake to handle large volumes of structured and unstructured data.
• Collaborate with cross-functional teams to develop robust data models and schemas that support business intelligence tools like Looker and other analytics platforms.
• Manage cloud-based databases on AWS, Azure, or other public cloud platforms, ensuring high availability, security, and performance.
• Develop and maintain APIs (Application Programming Interfaces) for seamless data access and integration across applications using RESTful services.
• Conduct data modeling activities utilizing dimensional modeling techniques for effective data warehousing design.
• Write complex SQL queries using Microsoft SQL Server, Oracle, or other SQL databases to support reporting and analysis needs.
• Support model training and analysis efforts by preparing datasets, performing exploratory data analysis, and applying analytical techniques.
• Automate routine tasks through shell scripting (Bash/Unix shell), VBA macros, or Python scripts to improve efficiency.
• Participate in Agile development cycles by collaborating with product owners, developers, and stakeholders to deliver high-quality solutions on time.

• Proven experience in software development with a strong focus on data engineering within big data environments.
• Extensive knowledge of cloud platforms such as AWS (Amazon Web Services), Azure Data Lake, or similar public cloud services.
• Proficiency in programming languages including Java and Python for data pipeline development and automation.
• Hands-on experience with big data technologies such as Hadoop, Spark, Apache Hive, and related ecosystems.
• Strong understanding of data management integration techniques including ETL processes using tools like Informatica or Talend.
• Expertise in designing scalable data models using dimensional modeling principles for enterprise data warehouses.
• Familiarity with business intelligence tools such as Looker for creating dashboards and reports.
• Solid understanding of SQL databases including Microsoft SQL Server, Oracle, and cloud-based database solutions like Azure SQL Database or similar.
• Knowledge of RESTful API development for integrating diverse systems efficiently.
• Experience with analytics techniques including model training and exploratory analysis to derive insights from complex datasets.
• Excellent problem-solving skills combined with the ability to communicate technical concepts clearly across teams.
• Ability to work in an Agile environment with a proactive approach to continuous improvement.