Senior Data Engineer at Tiger Analytics Inc.

Overview

Design and develop high-volume batch and real-time data pipelines for enterprise applications and analytics platforms. Build end-to-end data solutions covering ingestion transformation orchestration streaming and downstream delivery. Create scalable data processing solutions using distributed computing frameworks such as Spark EMR Hadoop or equivalent. Develop applications and data solutions using Java Python and SQL. Implement workflow orchestration and scheduling for complex data pipelines. Work with cloud data warehouse and cloud-native data platforms to support enterprise-scale workloads. Design solutions with a strong focus on reliability scalability performance security and low latency. Implement secure approaches for secrets management credentials and service-to-service authentication in production environments. Seeking 4+ years of experience building or operating enterprise-scale data pipelines and orchestration systems. Requires expertise in Java Python and SQL. Experience with real-time or event-driven data systems. Knowledge of distributed data technologies like Kafka Spark EMR Hadoop or equivalent. Familiarity with cloud data warehouse platforms at scale. Proficiency with major cloud platforms such as AWS Azure or GCP. Expertise in workflow orchestration tools like Airflow Control-M Autosys Step Functions or equivalent. Background in secure secrets management and credential handling. Agile engineering team experience. Understanding of distributed systems data processing and enterprise data architecture principles. Familiarity with data observability including monitoring alerting SLA management pipeline health and data quality. Strong problem-solving communication and collaboration skills.

What You'll Do18

• 1Design and develop high-volume batch and real-time data pipelines for enterprise applications and analytics platforms
• 2Build end-to-end data solutions covering ingestion transformation orchestration streaming and downstream delivery
• 3Develop event-driven and real-time data processing solutions using technologies such as Kafka and Spark
• 4Build scalable data processing solutions using distributed computing frameworks such as Spark EMR Hadoop or equivalent
• 5Develop applications and data solutions using Java Python and SQL
• 6Implement and manage workflow orchestration and scheduling for complex data pipelines
• 7Work with cloud data warehouse and cloud-native data platforms to support enterprise-scale workloads
• 8Design solutions with a strong focus on reliability scalability performance security and low latency
• 9Implement secure approaches for secrets management credentials and service-to-service authentication in production environments
• 104+ years of experience building or operating enterprise-scale data pipelines and orchestration systems
• 114+ years of data or application engineering experience with Java Python and SQL
• 124+ years of experience building and operating real-time or event-driven data systems
• 134+ years of experience with distributed data and computing technologies such as Kafka Spark EMR Hadoop or equivalent
• 144+ years of experience with cloud data warehouse/data platforms at scale
• 154+ years of experience with at least one major cloud platform AWS Azure or GCP
• 163+ years of experience with workflow orchestration and scheduling tools such as Airflow Control-M Autosys Step Functions or equivalent
• 172+ years of experience implementing secure secrets and credential management in production environments
• 182+ years of experience working in Agile engineering teams

Salary Insight