Backend Engineer (Data Engineering)

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Requirements:

• 7+ years of experience in software engineering with at least 4+ years focused on data engineering
• Strong experience with data processing frameworks (e.g., Spark, Kafka, Airflow), ETL workflows, and data modeling.
• Proficiency with both SQL and NoSQL databases, with experience optimizing queries and database performance.
• Familiarity with cloud data services (e.g., AWS Redshift, S3, Glue, EMR) and DevOps practices, including CI/CD for data pipelines.
• Strong coding abilities in Python, Java, or Scala with experience in data manipulation libraries.
• Strong analytical and problem-solving abilities, with a focus on delivering robust and scalable data solutions.
• Excellent communication skills and the ability to work effectively in a cross-functional team.
• Comfort working in a fast-paced startup environment with the ability to pivot and adapt as needed.

Responsibilities:

• Design, implement, and maintain scalable data pipelines that process large volumes of security data efficiently.
• Architect and develop backend data systems, ensuring they are scalable, maintainable, and secure.
• Take ownership of the entire data lifecycle, from ingestion and storage to processing and visualization.
• Work closely with other engineers, data scientists, and product managers to ensure data systems support product features and analytical needs.
• Continuously monitor and improve data processing performance, security, and scalability.
• Define and enforce data quality standards, processing methodologies, and documentation to maintain high-quality data systems.
• Quickly prototype and iterate on new data solutions, adapting to evolving requirements and emerging technologies.
• As the team grows, mentor junior engineers and lead by example in technical discussions and code reviews related to data systems.