Senior Data Engineer

Tiger Analytics Inc.•Dallas, TX
•Remote

About The Position

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. 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.

Requirements

  • Experience as a Data Engineer
  • Experience with Azure Data Factory, Azure Synapse, and Azure Databricks
  • Experience with ADLS Gen2, Delta Lake, and relational/NoSQL databases
  • Experience with high-volume batch data and real-time streaming workloads
  • Experience optimizing database queries, PySpark jobs, and data pipeline performance
  • Experience modeling dimensional data marts (Star/Snowflake schemas)
  • Experience with data governance, automated data quality validation, and end-to-end lineage tracking (e.g., via Microsoft Purview)
  • Experience with Azure Role-Based Access Control (RBAC), Key Vaults, and encryption standards
  • Experience with Azure DevOps, GitHub Actions, and CI/CD best practices

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

Benefits

  • Significant career development opportunities
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