Data Engineering Lead

Key Responsibilities: Develop and maintain the overall data architecture, ensuring data consistency, integrity, and security. Define the data strategy, aligning it with business objectives and technology roadmap. Establish data governance policies and procedures to ensure data quality and compliance. Lead and manage data engineering teams, providing guidance and mentorship. Oversee data engineering projects, ensuring they are delivered on time, within budget, and to the desired quality standards. Allocate resources effectively to meet project demands and maximize productivity. Design and develop robust data pipelines to extract, transform, and load (ETL) data from various sources into data warehouses or data lakes. Leverage data engineering tools and technologies (e.g., Apache Spark, Kafka, Hadoop, Python) to build scalable and efficient data pipelines. Automate data pipelines to improve efficiency and reduce manual effort. Implement data quality checks and monitoring processes to ensure data accuracy and consistency. Enforce data governance policies and standards to protect data privacy and security. Collaborate with data analysts and scientists to ensure data is prepared and accessible for analytics purposes. Support the development of data-driven insights and decision-making. Job Requirements: Proficiency in data engineering tools and technologies (e.g., Apache Spark, Kafka, Hadoop, Python). Experience with data warehousing and data lake architectures. Knowledge of cloud platforms (e.g., AWS, Azure, GCP) and their data services. Understanding of data quality concepts and tools. Ability to lead and motivate teams, providing guidance and mentorship. Strong problem-solving and analytical skills. Excellent communication skills, both verbal and written. Ability to think strategically and align data initiatives with business goals. Strong interpersonal skills and ability to build relationships with stakeholders. Experience leading data engineering teams or projects is a plus. Bachelor's degree in Computer Science, Data Science, or a related field. Data engineering certifications (e.g., AWS Certified Data Engineer, GCP Certified Professional Data Engineer) are preferred but not required. Minimum 3-4 years of relevant experience is required.