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Data Engineering Lead
1 month ago
Experience:10-15 years of experience in data engineering and AI Labs industryDemonstrated experience in leading and managing data engineering teamsProven track record of delivering complex data engineering projectsRoles and Responsibilities:Lead the design, development, and implementation of scalable and efficient data engineering solutionsManage and mentor a team of data engineers, providing technical guidance and leadershipCollaborate with cross-functional teams to understand business requirements and translate them into technical solutionsDrive innovation by evaluating and implementing new technologies and tools for data processing and analysisEnsure the reliability, security, and performance of data engineering systems and processesDevelop and maintain documentation for data engineering processes, standards, and best practicesStay updated with the latest industry trends and best practices in data engineering and AI LabsContribute to the overall data strategy and roadmap for the organizationEducation Qualification:Bachelor's or Master's degree in Computer Science, Engineering, or a related fieldCertification required:Professional certifications in data engineering or related fields are an advantageCloud Data Engineering certification from Azure or GCP.Behavioural Skills:Strong leadership and team management skillsExcellent communication and collaboration abilitiesProblem-solving mindset with a focus on innovationAdaptability and ability to work in a fast-paced and dynamic environmentStrong decision-making and strategic thinking capabilitiesTechnical Skills:Strong data engineering skills: Proficient in data modeling, ETL processes, and developing batch/real-time data pipelines.Programming expertise: Skilled in Python, Scala, and SQL.Big data experience: Hands-on experience with Hadoop, Spark, Kafka, Databricks, and Iceberg.Data governance and quality: Knowledgeable in data quality, governance, and security principles.Cloud platforms: Deep understanding of data engineering on AWS, Azure, or GCP.Database management: Experience with data warehousing solutions, SQL and NoSQL databases.ERP/System integration: Experienced with data connections from ERP systems like SAP, Oracle, SCADA, and OSI.Data analytics and ML: Understanding of machine learning concepts and data analysis techniques.Non-Negotiable Skills:Expertise in data modeling, ETL processes, and data pipeline developmentStrong leadership and team management skillsExcellent communication and collaboration abilities
