Senior Engineering Manager - Big Data

The candidate will have responsibilities across the following functions:

Team Leadership and Management:

• Lead, mentor, and grow a team of data application engineers.
• Set clear goals, provide regular feedback, and manage performance.
• Foster a collaborative, high-performing engineering culture.

Technical Strategy and Execution:

• Architect and implement robust, scalable applications using big data technologies.
• Partner with data scientists, analysts, and software engineers to deliver high-quality solutions.

Project and Stakeholder Management:

• Collaborate with cross-functional teams to understand business needs and translate them into technical requirements.
• Manage project timelines, prioritise tasks, and ensure timely delivery.
• Ensure compliance with data governance and security policies.

Process Improvement:

• Establish best practices for engineering, including testing, version control, and documentation.
• Evaluate and integrate new technologies and tools as appropriate.
• Continuously improve system performance, cost, and scalability.

Requirements:

• Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
• 9-12 years of experience in data engineering or software engineering.
• 4+ years of experience in a leadership or managerial role (should have managed at least 40-50 people and at least 2-3 EMs).
• Expertise in SQL and data modelling.
• Strong proficiency in Python, Scala, and Spark.
• Experience with data pipeline orchestration tools (e. g., Airflow).
• Familiarity with big data technologies (e. g., Spark, EMR).
• Experience with cloud platforms (e. g., AWS) and services like S3 and Redshift.
• Solid understanding of data warehousing concepts and real-time data streaming (e. g., Kafka).
• Excellent communication and interpersonal skills.
• Strong problem-solving skills and attention to detail.
• Ability to balance technical leadership with people management.

Skills

airflow, aws, emr, kafka, python, redshift, s3, scala, spark, sql