Senior Data Engineer at Tiger Analytics Inc.

Job description

About Tiger Analytics Shape the Future of AI. Transform the World's Leading Businesses. Tiger Analytics is one of the fastest-growing AI services firms, partnering with some of the world's largest and most influential organizations to redefine how business gets done. We help Fortune 500 companies harness the power of Artificial Intelligence, Generative AI, Data Science, Data Engineering and Advanced Analytics to solve their most complex challenges, unlock new growth opportunities, and create lasting business impact. We are at the forefront of the AI revolution, helping enterprises move beyond traditional analytics to embrace Generative AI, agentic AI, intelligent automation, and cloud-native data platforms. A global presence across North America, Latin America, Europe, and India. At Tiger Analytics, we don't just help businesses adapt to the future—we help them build it. What you will be doing We are looking for a Senior Azure Data Engineer with strong expertise in Microsoft Azure data services, Python, Scala, and Apache Spark. The ideal candidate will design, develop, and maintain scalable data pipelines and ETL/ELT solutions to support enterprise data platforms. Key Responsibilities: • Design, develop, and maintain scalable data pipelines using Azure data services, Python, Scala, and Apache Spark. • Develop and optimize ETL/ELT processes for data ingestion, transformation, and processing across diverse data sources. • Build and manage data pipelines using Azure Data Factory, Azure Databricks, and Azure Data Lake Storage. • Develop and optimize Spark applications to improve data processing performance, scalability, and reliability. • Work with Hadoop and related big data technologies where applicable. • Monitor pipeline execution, troubleshoot failures, and resolve data processing issues to ensure reliable data delivery. • Implement data validation, error handling, and data quality checks to ensure accuracy and consistency. • Collaborate with data architects, analysts, and cross-functional teams to understand requirements and deliver reliable data solutions. • Follow coding standards, testing practices, version control, and CI/CD procedures. • Support production deployments, incident resolution, performance tuning, and ongoing maintenance of data engineering solutions. What we need • Bachelor’s degree in Computer Science, Information Technology, Computer Engineering, or a related field. • 10+ years of overall Data Engineering experience. • Strong hands-on experience with Microsoft Azure data services, particularly Azure Data Factory, Azure Databricks, and Azure Data Lake Storage. • Proficiency in Python and Scala for data processing and application development. • Strong experience with Apache Spark and distributed data processing. • Hands-on experience with Hadoop and big data technologies. • Strong understanding of ETL/ELT processes, data transformations, and data pipeline architecture. • Strong SQL skills and experience with performance tuning, debugging, troubleshooting, and production support. • Experience with Control-M for batch scheduling, job monitoring, workflow orchestration, and dependency management. • Familiarity with version control, CI/CD, and deployment practices. • Excellent analytical, problem-solving, and collaboration skills. Why Join Tiger Analytics: • Drive High-Impact Business Transformation: Lead strategic engagements that go beyond traditional analytics, delivering enterprise-wide AI adoption, cloud-native data modernization, and measurable business outcomes. • Build and Lead at Global Scale: Collaborate with exceptional AI, data, engineering, and consulting talent across geographies to deliver transformative solutions and grow strategic client partnerships. • Benefits: Medical, Dental, Vision, Retirement Accounts, Long and Short Term Disability, Life Insurance, HSA/FSA Accounts (USA) and Discretionary time-off. • Continuous Learning & AI Upskilling: Stay ahead of the rapidly evolving AI landscape through continuous learning, hands-on exposure to emerging technologies, and opportunities to build expertise in Generative AI, agentic AI, and next-generation data platforms. Grow alongside a team that invests in developing future-ready skills and encourages innovation. Tiger Analytics provides equal employment opportunities to applicants and employees without regard to race, color, religion, age, sex, sexual orientation, gender identity/expression, pregnancy, national origin, ancestry, marital status, protected veteran status, disability status, or any other basis as protected by federal, state, or local law.

Requirements

Must-haves

Design, develop, and maintain scalable data pipelines using Azure data services, Python, Scala, and Apache Spark.
Develop and optimize ETL/ELT processes for data ingestion, transformation, and processing across diverse data sources.
Build and manage data pipelines using Azure Data Factory, Azure Databricks, and Azure Data Lake Storage.
Develop and optimize Spark applications to improve data processing performance, scalability, and reliability.
Work with Hadoop and related big data technologies where applicable.
Monitor pipeline execution, troubleshoot failures, and resolve data processing issues to ensure reliable data delivery.
Implement data validation, error handling, and data quality checks to ensure accuracy and consistency.
Collaborate with data architects, analysts, and cross-functional teams to understand requirements and deliver reliable data solutions.
Follow coding standards, testing practices, version control, and CI/CD procedures.
Support production deployments, incident resolution, performance tuning, and ongoing maintenance of data engineering solutions.
What we need
Bachelor’s degree in Computer Science, Information Technology, Computer Engineering, or a related field.
10+ years of overall Data Engineering experience.
Strong hands-on experience with Microsoft Azure data services, particularly Azure Data Factory, Azure Databricks, and Azure Data Lake Storage.
Proficiency in Python and Scala for data processing and application development.
Strong experience with Apache Spark and distributed data processing.
Hands-on experience with Hadoop and big data technologies.
Strong understanding of ETL/ELT processes, data transformations, and data pipeline architecture.
Strong SQL skills and experience with performance tuning, debugging, troubleshooting, and production support.
Experience with Control-M for batch scheduling, job monitoring, workflow orchestration, and dependency management.
Familiarity with version control, CI/CD, and deployment practices.
Excellent analytical, problem-solving, and collaboration skills.
Drive High-Impact Business Transformation: Lead strategic engagements that go beyond traditional analytics, delivering enterprise-wide AI adoption, cloud-native data modernization, and measurable business outcomes.
Build and Lead at Global Scale: Collaborate with exceptional AI, data, engineering, and consulting talent across geographies to deliver transformative solutions and grow strategic client partnerships.

Nice-to-haves

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Keywords to mirror

aiazurepythonci/cdsqlgo

Platform: workable
Effort: medium

Benefits

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Dental

Vision