Desenvolve e mantém pipelines de dados em AWS, Databricks e Cloudera, otimiza processamento distribuído com Spark e apoia áreas de negócio na implementação de soluções de dados.
Senior Data Engineer
📜 Description
- Design, develop, and maintain scalable data pipelines with Databricks, Apache Spark, Python, and Scala.
- Build and optimize ETL/ELT processes for data ingestion, transformation, and processing across diverse sources.
- Use Hadoop technologies to process structured and unstructured data at scale.
- Develop and tune Spark applications for performance, scalability, and reliability.
- Schedule and monitor batch jobs and workflow dependencies with Control-M; troubleshoot failures and pipeline issues.
- Implement data validation and quality checks, collaborate across teams, and support deployments, incident resolution, and ongoing maintenance.
🛠️ Requirements
- 8+ years of overall Data Engineering experience.
- Hands-on experience with Databricks, Apache Spark, Hadoop, and big data technologies.
- Proficiency in Python and Scala for data processing and application development.
- Experience with Control-M for batch scheduling, job monitoring, workflow orchestration, and dependency management.
- Strong understanding of ETL/ELT, data transformations, and distributed data processing.
- Experience with performance tuning, debugging, troubleshooting, and production support.
- Strong SQL skills and understanding of data management concepts.
- Analytical, problem-solving, and collaboration skills.
✨ Benefits
- Medical insurance
- Dental insurance
- Vision insurance
- Retirement accounts
- Long- and short-term disability coverage
- Life insurance
- HSA/FSA accounts (USA)
- Discretionary time off
Full 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 seeking a Senior Data Engineer to join our advanced analytics and AI team supporting some of our large enterprise clients. In this role, you will be responsible for designing, developing, and maintaining scalable data pipelines, processing large datasets, and managing scheduled data workflows to support enterprise data engineering initiatives.
Key Responsibilities:
- Design, develop, and maintain scalable data pipelines using Databricks, Apache Spark, Python, and Scala.
- Develop and optimize ETL/ELT processes for data ingestion, transformation, and processing across diverse data sources.
- Work with Hadoop and its ecosystem to process and manage large volumes of structured and unstructured data.
- Develop, troubleshoot, and optimize Spark applications to improve performance, scalability, and reliability.
- Use Control-M to schedule, monitor, and manage batch jobs, workflow dependencies, and data processing pipelines.
- Troubleshoot job failures, resolve data pipeline issues, and ensure timely completion of scheduled workloads.
- Implement data validation, error handling, and quality checks to ensure data 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 deployment procedures.
- Support production deployments, incident resolution, and ongoing maintenance of data engineering solutions.
Requirements
What we need
- 8+ years of overall Data Engineering experience.
- Strong hands-on experience with Databricks and Apache Spark.
- Proficiency in Python and Scala for data processing and application development.
- Hands-on experience with Hadoop and big data technologies.
- Experience with Control-M for batch scheduling, job monitoring, workflow orchestration, and dependency management.
- Strong understanding of ETL/ELT processes, data transformations, and distributed data processing.
- Experience in performance tuning, debugging, troubleshooting, and production support.
- Strong SQL skills and understanding of data management concepts.
- Excellent analytical, problem-solving, and collaboration skills.
Benefits
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.
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