Senior Cloud Data Architect

2 days ago

Delhi, Delhi, India beBeeDataEngineer Full time ₹ 10,00,000 - ₹ 15,00,000
About Us

We're seeking a skilled Senior Data Engineer with expertise in Apache Spark and Databricks to lead our data engineering efforts. You will be responsible for designing, developing, and optimizing scalable data pipelines and applications using modern cloud technologies.

Responsibilities:
  • Data Pipeline Development: Design, develop, and implement scalable data pipelines and applications using Apache Spark and Databricks, adhering to industry best practices.
  • Data Integration: Integrate data from multiple source systems, including legacy warehouses, modern cloud data platforms, streaming systems, and APIs.
  • Architecture Optimization: Apply Lambda and Kappa architectures where appropriate to balance real-time and batch processing needs.
  • Troubleshooting: Troubleshoot complex issues related to data ingestion, transformation, and pipeline execution, ensuring data quality, lineage, and governance practices are embedded into data pipelines.
  • Data Modeling: Work with data modeling teams to implement canonical models, such as customer, contract, usage, and network models.
  • Regulatory Compliance: Implement and monitor consent management and regulatory compliance GDPR in data pipelines.
  • Performance Tuning: Perform in-depth performance tuning and optimization of Spark applications within the Databricks environment.
  • Cross-Functional Collaboration: Collaborate with cross-functional teams, including data scientists, analysts, and architects, to deliver end-to-end data solutions.
  • Technology Evaluation: Continuously evaluate and adopt new technologies and tools in the Databricks and cloud ecosystem.
  • Ongoing Improvement: Collaborate with DataOps, architects, and monitoring teams to establish observability and incident management practices.
  • Documentation: Document technical designs, development processes, and operational procedures.
Requirements:
  • Bachelor's degree in Computer Science, Engineering, or a related field.
  • 10+ years of experience in data engineering or big data development.
  • 6+ years of hands-on experience with Apache Spark and Databricks.
  • Deep understanding of Spark internals, Spark Streaming, Kafka, and Delta Lake.
  • Experience designing Lambda and/or Kappa architectures for hybrid batch + streaming data processing.
  • Experience in developing solutions using Azure Data Services, including Azure Databricks, Azure Data Factory, Azure DevOps, Azure Functions, Event/Message services, and Azure SQL Database.
  • Proficient in PySpark or Scala.
  • Strong experience with open-source big data technologies, including Apache Flink, Airflow, Nifi, Kafka, etc.
  • Strong experience in performance tuning, cost optimization, and cluster management in Databricks.
  • Solid understanding of data warehousing, ETL/ELT pipelines, and data modeling.
  • Experience working with cloud platforms (Azure preferred; AWS/GCP is a plus).
  • Familiarity with governance and compliance frameworks (e.g., GDPR, PII, consent management).
  • Familiarity with Agile/Scrum methodologies.
  • Proficiency in German and English (written and verbal).

Preferred Qualifications:
- Databricks Certified Professional Data Engineer certification is a strong plus.
- Strong communication skills - both written and verbal - with the ability to convey technical concepts to non-technical stakeholders.
- Proven ability to work independently as well as in a team-oriented, collaborative environment.

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