SeniorLead Data Engineer Databricks

Gurgaon - India

Monthly Salary: Not Disclosed

Posted on: 30+ days ago

Vacancies: 1 Vacancy

Job Summary

Senior/Lead Data Engineer - Databricks

We are seeking a highly skilled and experienced Data Engineering Lead with a strong background in the retail domain and exceptional programming abilities. As a Lead you will play a pivotal role in implementing and optimizing data architecture to support our retail business operations and analytics initiatives. Your expertise in Spark programming optimization techniques and familiarity with Databricks and CI/CD practices will be instrumental in ensuring the efficient and effective management of our dataecosystem.

Imp Pointers as below skills should be in the CV

Data Platform (Data Engineers)

Data Lake:AWS S3 / Azure / Dell Cloud Data Lake with Delta Lake format
Data Warehouse:Databricks IOMETE Google BigQuery for analytical workloads
Batch Processing /Stream Processing:Batch/real-time processing of data pipelines
Database:PostgreSQL for transactional data NoSQL (ex. MongoDB Cassendra) for document storage

Responsibilities:

Design and develop data models data integration processes and data pipelines to capture transform and load structured and unstructured data from various retail sources.
Hands-on programming in Spark to develop and optimize data processing applications and analytics workflows.
Apply optimization techniques to enhance the performance and efficiency of data processing and analytical tasks.
Evaluate and implement appropriate tools and technologies including Databricks to streamline data operations and ensure scalability and reliability.
Work closely with other team members to ensure data integrity consistency and accessibility across the organization.
Define and enforce best practices for data governance and data management including data quality metadata management and data security.
Collaborate with DevOps teams to establish and maintain CI/CD pipelines for data engineering and analytics workflows.
Peer Review of team members deliverables
Stay updated with the latest advancements and trends in the retail domain data architecture and programming languages to drive continuous improvement.

Requirements:

At least 5 years of experience in the data engineering domain.
Proven experience as a senior Data Engineer /Lead preferably within the retail industry.
Strong programming skills with expertise in PySpark programming and optimization techniques.
Hands-on experience with Databricks Deltalake and its components for data processing and analytics.
Hands-on experience in data modelling data integration and ETL/ELT processes.
Experience in working with Gitlab pipelines and an in-depth understanding of CI/CD pipeline designs.
Experience with data governance data quality and metadata management.
Strong analytical and problem-solving abilities with a detail-oriented mindset.
Excellent communication and collaboration skills to work effectively with cross-functional teams.
Ability to adapt to a fast-paced and evolving environment while managing multiple priorities.
Good to have experience in at least one of the Cloud Vendor (AWS / Azure / GCP)
Good to have experience with streaming technologies as well

Required Experience:

Senior IC

Senior/Lead Data Engineer - DatabricksWe are seeking a highly skilled and experienced Data Engineering Lead with a strong background in the retail domain and exceptional programming abilities. As a Lead you will play a pivotal role in implementing and optimizing data architecture to support our reta...

Senior/Lead Data Engineer - Databricks

Imp Pointers as below skills should be in the CV

Data Platform (Data Engineers)

Data Lake:AWS S3 / Azure / Dell Cloud Data Lake with Delta Lake format
Data Warehouse:Databricks IOMETE Google BigQuery for analytical workloads
Batch Processing /Stream Processing:Batch/real-time processing of data pipelines
Database:PostgreSQL for transactional data NoSQL (ex. MongoDB Cassendra) for document storage

Responsibilities:

Design and develop data models data integration processes and data pipelines to capture transform and load structured and unstructured data from various retail sources.
Hands-on programming in Spark to develop and optimize data processing applications and analytics workflows.
Apply optimization techniques to enhance the performance and efficiency of data processing and analytical tasks.
Evaluate and implement appropriate tools and technologies including Databricks to streamline data operations and ensure scalability and reliability.
Work closely with other team members to ensure data integrity consistency and accessibility across the organization.
Define and enforce best practices for data governance and data management including data quality metadata management and data security.
Collaborate with DevOps teams to establish and maintain CI/CD pipelines for data engineering and analytics workflows.
Peer Review of team members deliverables
Stay updated with the latest advancements and trends in the retail domain data architecture and programming languages to drive continuous improvement.

Requirements:

At least 5 years of experience in the data engineering domain.
Proven experience as a senior Data Engineer /Lead preferably within the retail industry.
Strong programming skills with expertise in PySpark programming and optimization techniques.
Hands-on experience with Databricks Deltalake and its components for data processing and analytics.
Hands-on experience in data modelling data integration and ETL/ELT processes.
Experience in working with Gitlab pipelines and an in-depth understanding of CI/CD pipeline designs.
Experience with data governance data quality and metadata management.
Strong analytical and problem-solving abilities with a detail-oriented mindset.
Excellent communication and collaboration skills to work effectively with cross-functional teams.
Ability to adapt to a fast-paced and evolving environment while managing multiple priorities.
Good to have experience in at least one of the Cloud Vendor (AWS / Azure / GCP)
Good to have experience with streaming technologies as well