Data Engineering Manager

Key Responsibilities: Lead and mentor a team of data engineers, fostering a high-performance and collaborative culture. Design, build, and optimize scalable, robust, and secure ETL/ELT pipelines for data ingestion, transformation, and integration from various sources. Oversee the development and maintenance of data lakes , data warehouses , and real-time streaming data platforms . Collaborate with data scientists, analysts, and product teams to understand data requirements and deliver reliable data solutions. Ensure high data quality, data governance, and adherence to privacy and compliance standards (GDPR, HIPAA, etc.). Establish best practices in data architecture, engineering, and DevOps processes. Evaluate and implement new tools and technologies to improve efficiency and scalability. Monitor and improve data pipeline performance and cost-efficiency in cloud or hybrid environments. Define and track KPIs related to data engineering performance and reliability. Own the roadmap for data engineering initiatives and align it with business and technical goals. Qualifications and Requirements: Bachelor's or Master's degree in Computer Science, Data Engineering, Information Systems, or a related field. 7+ years of experience in data engineering or data platform development. 2+ years of experience in a technical leadership or management role. Strong programming skills in Python, Java, or Scala . Proficient in SQL and working with large-scale structured and unstructured data. Deep experience with modern data tools and platforms such as: Apache Spark, Kafka, Airflow Snowflake, Redshift, BigQuery, or Databricks Data modeling tools and data cataloging systems Hands-on experience with cloud platforms (AWS, Azure, GCP) and data services. Experience with CI/CD, containerization (Docker, Kubernetes), and infrastructure-as-code. Excellent problem-solving, communication, and stakeholder management skills.