Senior Data Engineer

Tiger Analytics is a fast-growing advanced analytics consulting firm. Our consultants bring deep expertise in Data Science, Machine Learning and AI. We are the trusted analytics partner for multiple Fortune 500 companies, enabling them to generate business value from data. Our business value and leadership has been recognized by various market research firms, including Forrester and Gartner. We are looking for top-notch talent as we continue to build the best global analytics consulting team in the world.

Tiger Analytics is looking for an experienced Data Engineer to design, build, and operate large-scale batch and real-time data pipelines that power enterprise data and analytics platforms.

You will work closely with Agile engineering, architecture, and product teams to build reliable, scalable data solutions spanning data ingestion, transformation, orchestration, event streaming, and downstream data delivery. The ideal candidate is someone who enjoys solving complex data engineering problems and building highly available systems that operate at enterprise scale.

Key Responsibilities:

• 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.
• Develop event-driven and real-time data processing solutions using technologies such as Kafka and Spark.
• Build scalable data processing solutions using distributed computing frameworks such as Spark, EMR, Hadoop, or equivalent technologies.
• Develop applications and data solutions using Java, Python, and SQL.
• Implement and manage 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.

• 4+ years of experience building or operating enterprise-scale data pipelines and orchestration systems.
• 4+ years of data or application engineering experience with Java, Python, and SQL.
• 4+ years of experience building and operating real-time or event-driven data systems.
• 4+ years of experience with distributed data and computing technologies such as Kafka, Spark, EMR, Hadoop, or equivalent.
• 4+ years of experience working with cloud data warehouse/data platforms at scale.
• 4+ years of experience with at least one major cloud platform: AWS, Azure, or GCP.
• 3+ years of experience with workflow orchestration and scheduling tools such as Airflow, Control-M, Autosys, Step Functions, or equivalent.
• 2+ years of experience implementing secure secrets and credential management in production environments.
• 2+ years of experience working in Agile engineering teams.
• Strong 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.