Noida, Uttar Pradesh

Job Summary

Job Title: Senior Data Engineer (Databricks, PySpark & Python) Job Summary We are seeking a highly skilled Senior Data Engineer with expertise in Databricks, PySpark, Python, and Big Data technologies. The ideal candidate will have hands-on experience building scalable data platforms, developing high-performance data pipelines, and implementing modern data architectures using Databricks Lakehouse. The role requires strong knowledge of Medallion Architecture, Unity Catalog, and enterprise data governance practices. ey Responsibilities • Design, develop, and maintain scalable data pipelines and ETL/ELT solutions.

- Build and optimize batch and streaming data processing solutions using PySpark and Databricks.
- Implement and manage Medallion Architecture (Bronze, Silver, Gold layers) for data transformation and consumption.
- Configure and manage Unity Catalog for centralized governance, access control, and data lineage.
- Develop robust data engineering solutions using Python and Spark frameworks.
- Optimize Databricks workloads for performance, scalability, and cost efficiency.
- Collaborate with data architects, analysts, data scientists, and business stakeholders to deliver high-quality data solutions.
- Ensure data quality, security, governance, and compliance across enterprise data platforms.
- Support Data Lake, Lakehouse, and Data Warehouse initiatives.
- Troubleshoot and resolve complex data engineering and performance issues. ________________________________________ Required Skills &

Qualifications • Strong hands-on experience with Databricks and Databricks Lakehouse Platform.

- Expert-level proficiency in Python programming.
- Deep expertise in PySpark and distributed data processing.
- Strong understanding of Big Data concepts and modern data architectures.
- Good understanding and practical implementation experience of Medallion Architecture (Bronze, Silver, Gold layers).
- Experience working with Unity Catalog for data governance, security, access management, and lineage tracking.
- Strong knowledge of Apache Spark performance tuning and optimization.
- Experience in designing and building scalable ETL/ELT pipelines.
- Hands-on experience with Delta Lake and Lakehouse architecture.
- Experience with cloud platforms such as Azure, AWS, or GCP.
- Strong analytical, problem-solving, and communication skills.

Key Responsibilities

Job Title: Senior Data Engineer (Databricks, PySpark & Python) Job Summary We are seeking a highly skilled Senior Data Engineer with expertise in Databricks, PySpark, Python, and Big Data technologies. The ideal candidate will have hands-on experience building scalable data platforms, developing high-performance data pipelines, and implementing modern data architectures using Databricks Lakehouse. The role requires strong knowledge of Medallion Architecture, Unity Catalog, and enterprise data governance practices. ________________________________________ Key Responsibilities • Design, develop, and maintain scalable data pipelines and ETL/ELT solutions.

- Build and optimize batch and streaming data processing solutions using PySpark and Databricks.
- Implement and manage Medallion Architecture (Bronze, Silver, Gold layers) for data transformation and consumption.
- Configure and manage Unity Catalog for centralized governance, access control, and data lineage.




- Develop robust data engineering solutions using Python and Spark frameworks.
- Optimize Databricks workloads for performance, scalability, and cost efficiency.
- Collaborate with data architects, analysts, data scientists, and business stakeholders to deliver high-quality data solutions.
- Ensure data quality, security, governance, and compliance across enterprise data platforms.
- Support Data Lake, Lakehouse, and Data Warehouse initiatives.
- Troubleshoot and resolve complex data engineering and performance issues. ________________________________________ Required Skills &

Qualifications • Strong hands-on experience with Databricks and Databricks Lakehouse Platform.

- Expert-level proficiency in Python programming.
- Deep expertise in PySpark and distributed data processing.
- Strong understanding of Big Data concepts and modern data architectures.
- Good understanding and practical implementation experience of Medallion Architecture (Bronze, Silver, Gold layers).
- Experience working with Unity Catalog for data governance, security, access management, and lineage tracking.
- Strong knowledge of Apache Spark performance tuning and optimization.
- Experience in designing and building scalable ETL/ELT pipelines.
- Hands-on experience with Delta Lake and Lakehouse architecture.
- Experience with cloud platforms such as Azure, AWS, or GCP.
- Strong analytical, problem-solving, and communication skills.

Skill Requirements

Job Title: Senior Data Engineer (Databricks, PySpark & Python) Job Summary We are seeking a highly skilled Senior Data Engineer with expertise in Databricks, PySpark, Python, and Big Data technologies. The ideal candidate will have hands-on experience building scalable data platforms, developing high-performance data pipelines, and implementing modern data architectures using Databricks Lakehouse. The role requires strong knowledge of Medallion Architecture, Unity Catalog, and enterprise data governance practices. ________________________________________ Key Responsibilities • Design, develop, and maintain scalable data pipelines and ETL/ELT solutions.

- Build and optimize batch and streaming data processing solutions using PySpark and Databricks.
- Implement and manage Medallion Architecture (Bronze, Silver, Gold layers) for data transformation and consumption.
- Configure and manage Unity Catalog for centralized governance, access control, and data lineage.
- Develop robust data engineering solutions using Python and Spark frameworks.
- Optimize Databricks workloads for performance, scalability, and cost efficiency.
- Collaborate with data architects, analysts, data scientists, and business stakeholders to deliver high-quality data solutions.
- Ensure data quality, security, governance, and compliance across enterprise data platforms.
- Support Data Lake, Lakehouse, and Data Warehouse initiatives.
- Troubleshoot and resolve complex data engineering and performance issues.Required Skills &

Qualifications • Strong hands-on experience with Databricks and Databricks Lakehouse Platform.





- Expert-level proficiency in Python programming.
- Deep expertise in PySpark and distributed data processing.
- Strong understanding of Big Data concepts and up-to-date data architectures.
- Good understanding and practical implementation experience of Medallion Architecture (Bronze, Silver, Gold layers).
- Experience working with Unity Catalog for data governance, security, access management, and lineage tracking.
- Strong knowledge of Apache Spark performance tuning and optimization.
- Experience in designing and building scalable ETL/ELT pipelines.
- Hands-on experience with Delta Lake and Lakehouse architecture.
- Experience with cloud platforms such as Azure, AWS, or GCP.
- Strong analytical, problem-solving, and communication skills.

Other Requirements

Job Title: Senior Data Engineer (Databricks, PySpark & Python) Job Summary We are seeking a highly skilled Senior Data Engineer with expertise in Databricks, PySpark, Python, and Big Data technologies. The ideal candidate will have hands-on experience building scalable data platforms, developing high-performance data pipelines, and implementing modern data architectures using Databricks Lakehouse. The role requires strong knowledge of Medallion Architecture, Unity Catalog, and enterprise data governance practices.

Key Responsibilities • Design, develop, and maintain scalable data pipelines and ETL/ELT solutions.

- Build and optimize batch and streaming data processing solutions using PySpark and Databricks.
- Implement and manage Medallion Architecture (Bronze, Silver, Gold layers) for data transformation and consumption.
- Configure and manage Unity Catalog for centralized governance, access control, and data lineage.
- Develop robust data engineering solutions using Python and Spark frameworks.
- Optimize Databricks workloads for performance, scalability, and cost efficiency.
- Collaborate with data architects, analysts, data scientists, and business stakeholders to deliver high-quality data solutions.
- Ensure data quality, security, governance, and compliance across enterprise data platforms.
- Support Data Lake, Lakehouse, and Data Warehouse initiatives.
- Troubleshoot and resolve complex data engineering and performance issues. ________________________________________ Required Skills &

Qualifications • Strong hands-on experience with Databricks and Databricks Lakehouse Platform.

- Expert-level proficiency in Python programming.
- Deep expertise in PySpark and distributed data processing.
- Strong understanding of Big Data concepts and modern data architectures.
- Good understanding and practical implementation experience of Medallion Architecture (Bronze, Silver, Gold layers).
- Experience working with Unity Catalog for data governance, security, access management, and lineage tracking.
- Strong knowledge of Apache Spark performance tuning and optimization.
- Experience in designing and building scalable ETL/ELT pipelines.
- Hands-on experience with Delta Lake and Lakehouse architecture.
- Experience with cloud platforms such as Azure, AWS, or GCP.
- Strong analytical, problem-solving, and communication skills.

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📌 SME - Python (Noida)
🏢 HCLTech
📍 Noida