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.