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 Lead Data Engineer to design, build, and optimize scalable data platforms and real-time data solutions. The ideal candidate will have strong hands-on expertise in Python, SQL, cloud platforms, distributed data processing, streaming technologies, and modern cloud data warehouses.

Key Responsibilities:

• Lead the design and development of scalable batch and real-time data pipelines using Python and SQL.
• Design and implement data solutions on AWS, Azure, or GCP.
• Build high-volume data processing solutions using Spark, Kafka, Hadoop, EMR, or equivalent distributed technologies.
• Develop and optimize real-time and event-driven streaming applications.
• Design data models and structures supporting enterprise data warehouses and analytics platforms.
• Work with modern cloud data platforms such as Snowflake, Databricks, and Amazon Redshift.
• Optimize data pipelines and processing workloads for performance, scalability, reliability, and cost efficiency.
• Lead technical discussions, design reviews, and provide guidance to other data engineers.
• Collaborate with architects, product teams, application developers, and business stakeholders to translate requirements into scalable data solutions.
• Establish engineering best practices around code quality, testing, deployment, monitoring, and data quality