Lead Databricks Architect

Nityo Infotech
Iselin, NJ

Role : Lead Databricks Architect

Location : Iselin NJ : Hybrid (2-3 Days) Local candidates only

Duration : Contract

Must have : Expert in Databricks , Pyspark , python, SQL

JD:

  • Strong knowledge on data bricks architecture and tools
  • Have experience of task and wf jobs creations in data bricks.
  • Deep understanding of distributed computing and how to use spark for data processing.
  • SQL and pyspark : strong command over querying databases and proficiency in pyspark.
  • Cloud platform: Preferred Azure for data bricks deployment.
  • Qualifications
  • Bachelor's degree in Computer Science, Engineering, or related field, or equivalent work experience
  • 5+ years of experience in data engineering with Databricks and Spark
  • Proficient in SQL and Python and Pyspark
  • Experience with Azure Databricks Medallion Architecture with DLT, Iceberg
  • Financial/Corporate Banking context would be a plus
  • Experience with data integration and ETL tools, such as Azure Data Factory
  • Experience with Azure cloud platform and services
  • Experience with data warehouse and data lake concepts and architectures
  • Good to have experience with big data technologies, such as Kafka, Hadoop, Hive, etc
  • Strong analytical and problem-solving skills
  • Excellent communication and teamwork skills

Responsibilities

  • Design, develop, and maintain data pipelines using Databricks and Spark, and other cloud technologies as needed
  • Optimize data pipelines for performance, scalability, and reliability
  • Ensure data quality and integrity throughout the data lifecycle
  • Collaborate with data scientists, analysts, and other stakeholders to understand and meet their data needs
  • Troubleshoot and resolve data-related issues, and provide root cause analysis and recommendations
  • Document data pipeline specifications, requirements, and enhancements, and communicate them effectively to the team and management
  • Create new data validation methods and data analysis tools, and share best practices and learnings with the data engineering community
  • Implement ETL processes and data warehouse solutions, and ensure compliance with data governance and security policies
Posted 2025-07-28

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