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 several Fortune 100 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 analytics global consulting team in the world.
We are seeking an experienced Data Engineer to join our data team. In this role, you will be responsible for designing, building, and maintaining scalable data pipelines, data integration processes, and data infrastructure on AWS cloud. You will collaborate closely with data scientists, analysts, and AI teams to support analytics, machine learning, and Generative AI initiatives across the organization.
Key Responsibilities:
• Design, build, and maintain scalable ETL/ELT pipelines using Azure Data Factory, Azure Synapse, and Azure Databricks.
• Architect and manage secure enterprise cloud storage, including ADLS Gen2, Delta Lake, and relational/NoSQL databases.
• Ingest and process both high-volume batch data and real-time streaming workloads.
• Optimize database queries, PySpark jobs, and data pipeline performance to minimize execution time and cloud costs.
• Collaborate with BI and analytics teams to model dimensional data marts (Star/Snowflake schemas) for reporting.
• Implement data governance, automated data quality validation, and end-to-end lineage tracking (e.g., via Microsoft Purview ).
• Secure data pipelines and storage using Azure Role-Based Access Control (RBAC), Key Vaults, and encryption standards.
• Automate infrastructure deployments and code releases using Azure DevOps, GitHub Actions, and CI/CD best practices