What are the responsibilities and job description for the Sr. Azure Data Engineer position at Noblesoft Technologies?
Job Title: Azure Data Engineer
Location: Onsite: Greenfield, IN
Duration: FTE
Key Fields
Inputs
Educational Qualification*
Any Bachelor's Degree
Experience Range
10 years
Tagline/Tech Stack Snapshot -
Azure Databricks | PySpark | ADF | ADLS Gen2 | Azure SQL | Python | Unity Catalog | Delta Lake | Azure Cloud | CI/CD | Git | Azure DevOps
Role Summary - (To be filled by Practice /DO)
We are looking for an experienced Data Engineering Tech Lead with strong expertise in Azure Databricks, PySpark, Azure Data Factory (ADF), ADLS Gen2, Azure SQL, Python, and Azure Cloud. The role will lead the design, development, optimization, and maintenance of scalable enterprise data engineering and Lakehouse solutions, including batch and near-real-time data processing.
Primary (Must have skills)* - To be Screened by TA Team
4 years of experience in Azure Databricks with PySpark.
2 years of experience in Databricks workflow & Unity catalog.
3 years of experience in ADF (Azure Data Factory).
3 years of experience in ADLS Gen 2.
3 years of experience in Azure SQL.
5 years of experience in Azure Cloud platform.
2 years of experience in Python programming & package builds.
Why This Role Matters - New addition (To be filled by Practice /DO)
The Azure Data Engineering platform is a critical backbone for scalable, secure, and reliable enterprise data processing and analytics.
This Role Ensures
Reliable and scalable data pipelines across enterprise data sources
High-performance data processing using Databricks, PySpark, and ADF
Strong data governance, security, and quality across the Lakehouse
Continuous technical leadership, optimization, and modernization of the data platform
What You'll Do/
Job Description of Role* (RNR) - To be Evaluated by Technical Panel (Define it to give more clarity)
Key Technical Skills
Data management experience handling Analytics workload covering design, development, and maintainenance of lakehouse solutions sourcing data from platforms such as ERP sources, API sources, Relational stores, NoSQL and on-prem sources using Databricks/PySpark as distributed /big data management service,supporting batch and near-real-time ingestion, transformation, and processing.
Ability to optimize Spark jobs and manage large-scale data processing using RDD/DataFrame APIs.Demonstrated expertise in partitioning strategies, file format optimization (Parquet/Delta), and Spark SQL tuning.Familiarity with Databricks runtime versions, cluster policies, libraries, and workspace management.
Skilled in governing and manage data access for Azure Data lakehouse with Unity Catalog. Experience in configuring data permissions, object lineage, and access policies with Unity Catalog.Understanding of integrating Unity Catalog with Azure AD, external metastores, and audit trails.
Experience in building efficient orchestration solutions using Azure data factory, Databricks Workflows.Ability to design modular, reusable workflows using tasks, triggers, and dependencies.Skilled in using dynamic expressions, parameterized pipelines, custom activities, and triggers.
Familiarity with integration runtime configurations, pipeline performance tuning, and error handling strategies.
Strong experience in implementing secure, hierarchical namespace-based data lake storage for structured/semi-structured data, aligned to bronze-silver-gold layers with ADLS Gen2. Hands-on experience with lifecycle policies, access control (RBAC/ACLs), and folder-level security. Understanding of best practices in file partitioning, retention management, and storage performance optimization.
Capable of developing T-SQL queries, stored procedures, and managing metadata layers on Azure SQL.
Comprehensive experience working across the Azure ecosystem, including networking, security, monitoring, and cost management relevant to data engineering workloads.Understanding of VNets, Private Endpoints, Key Vaults, Managed Identities, and Azure Monitor.Exposure to DevOps tools for deployment automation (e.g., Azure DevOps, ARM/Bicep/Terraform).
Experience in writing modular, testable Python code used in data transformations, utility functions, and packaging reusable components.Familiarity with Python environments, dependency management (pip/Poetry/Conda), and packaging libraries.Ability to write unit tests using PyTest/unittest and integrate with CI/CD pipelines.
Lead solution design discussions, mentor junior engineers, and ensure adherence to coding guidelines, design patterns, and peer review processes.Able to prepare Design documents for development and guiding the team technically. Experience preparing technical design documents, HLD/LLDs, and architecture diagrams.Familiarity with code quality tools (e.g., SonarQube, pylint), and version control workflows (Git).
Demonstrates strong verbal and written communication, proactive stakeholder engagement, and a collaborative attitude in cross-functional teams.Ability to articulate technical concepts clearly to both technical and business audiences.Experience in working with product owners, QA, and business analysts to translate requirements into deliverables.
Soft skills/other skills - To be Evaluated by Hiring Manager (To define how this will be evaluated)
Communication Skills
Communicate effectively with internal and customer stakeholders
Communication approach: verbal, emails and instant messages
Interpersonal Skills
Strong interpersonal skills to build and maintain productive relationships with team members
Provide constructive feedback during code reviews and be open to receiving feedback on your own code.
Problem-Solving And Analytical Thinking
Capability to troubleshoot and resolve issues efficiently.
Analytical mindset.
Task/ Work Updates
Prior experience in working on Agile/Scrum projects with exposure to tools like Jira/Azure DevOps.
Provides regular updates, proactive and due diligent to carry out responsibilities.
What Success Looks Like (6 12 Months) -
Expected Outcome
We are seeking a highly skilled Data Engineering specialist with above mentioned mentioned Primary Skills to join our dynamic team who are at the forefront of enabling enterprises in Healthcare sectors.
The ideal candidate should be passionate about working on Data Engineering on Azure cloud with strong focus on DevOps practices in building product for our customers.
Effectively Communicate and Collaborate with internal teams and customer to build code leveraging or building low level design documents aligning to standard coding principles and guidelines.
Secondary Skills (Good to have)
Good to have Azure Entra/AD skills and GitHub Actions.
Good to have orchestration experience using Airflow, Dagster, LogicApp.
Good to have expereince working on event-driven architectures using Kafka, Azure Event Hub.
Good to have exposure on Google Cloud Pub/Sub.
Good to have experience developing and maintaining Change Data Capture (CDC) solutions preferrably using Debezium.
Good to have hands-on experience on data migration projects specifically involving Azure Synapse and Databricks Lakehouse.
Good to have eperienced in managing cloud storage solutions on Azure Data Lake Storage . Experience with Google Cloud Storage will be an advantage.
Why Join Us - New Addition
Join a team driving modern Azure Data Engineering and Lakehouse transformation using Databricks, PySpark, ADF, and cloud-native technologies.
This Role Offers
Opportunity to work on enterprise-scale Azure data platforms
Hands-on exposure to Databricks, PySpark, ADF, and Lakehouse architecture
Ownership of solution design and technical decisions
Opportunity to lead, mentor, innovate, and drive engineering best practices
Location: Onsite: Greenfield, IN
Duration: FTE
Key Fields
Inputs
Educational Qualification*
Any Bachelor's Degree
Experience Range
10 years
Tagline/Tech Stack Snapshot -
Azure Databricks | PySpark | ADF | ADLS Gen2 | Azure SQL | Python | Unity Catalog | Delta Lake | Azure Cloud | CI/CD | Git | Azure DevOps
Role Summary - (To be filled by Practice /DO)
We are looking for an experienced Data Engineering Tech Lead with strong expertise in Azure Databricks, PySpark, Azure Data Factory (ADF), ADLS Gen2, Azure SQL, Python, and Azure Cloud. The role will lead the design, development, optimization, and maintenance of scalable enterprise data engineering and Lakehouse solutions, including batch and near-real-time data processing.
Primary (Must have skills)* - To be Screened by TA Team
4 years of experience in Azure Databricks with PySpark.
2 years of experience in Databricks workflow & Unity catalog.
3 years of experience in ADF (Azure Data Factory).
3 years of experience in ADLS Gen 2.
3 years of experience in Azure SQL.
5 years of experience in Azure Cloud platform.
2 years of experience in Python programming & package builds.
Why This Role Matters - New addition (To be filled by Practice /DO)
The Azure Data Engineering platform is a critical backbone for scalable, secure, and reliable enterprise data processing and analytics.
This Role Ensures
Reliable and scalable data pipelines across enterprise data sources
High-performance data processing using Databricks, PySpark, and ADF
Strong data governance, security, and quality across the Lakehouse
Continuous technical leadership, optimization, and modernization of the data platform
What You'll Do/
Job Description of Role* (RNR) - To be Evaluated by Technical Panel (Define it to give more clarity)
Key Technical Skills
Data management experience handling Analytics workload covering design, development, and maintainenance of lakehouse solutions sourcing data from platforms such as ERP sources, API sources, Relational stores, NoSQL and on-prem sources using Databricks/PySpark as distributed /big data management service,supporting batch and near-real-time ingestion, transformation, and processing.
Ability to optimize Spark jobs and manage large-scale data processing using RDD/DataFrame APIs.Demonstrated expertise in partitioning strategies, file format optimization (Parquet/Delta), and Spark SQL tuning.Familiarity with Databricks runtime versions, cluster policies, libraries, and workspace management.
Skilled in governing and manage data access for Azure Data lakehouse with Unity Catalog. Experience in configuring data permissions, object lineage, and access policies with Unity Catalog.Understanding of integrating Unity Catalog with Azure AD, external metastores, and audit trails.
Experience in building efficient orchestration solutions using Azure data factory, Databricks Workflows.Ability to design modular, reusable workflows using tasks, triggers, and dependencies.Skilled in using dynamic expressions, parameterized pipelines, custom activities, and triggers.
Familiarity with integration runtime configurations, pipeline performance tuning, and error handling strategies.
Strong experience in implementing secure, hierarchical namespace-based data lake storage for structured/semi-structured data, aligned to bronze-silver-gold layers with ADLS Gen2. Hands-on experience with lifecycle policies, access control (RBAC/ACLs), and folder-level security. Understanding of best practices in file partitioning, retention management, and storage performance optimization.
Capable of developing T-SQL queries, stored procedures, and managing metadata layers on Azure SQL.
Comprehensive experience working across the Azure ecosystem, including networking, security, monitoring, and cost management relevant to data engineering workloads.Understanding of VNets, Private Endpoints, Key Vaults, Managed Identities, and Azure Monitor.Exposure to DevOps tools for deployment automation (e.g., Azure DevOps, ARM/Bicep/Terraform).
Experience in writing modular, testable Python code used in data transformations, utility functions, and packaging reusable components.Familiarity with Python environments, dependency management (pip/Poetry/Conda), and packaging libraries.Ability to write unit tests using PyTest/unittest and integrate with CI/CD pipelines.
Lead solution design discussions, mentor junior engineers, and ensure adherence to coding guidelines, design patterns, and peer review processes.Able to prepare Design documents for development and guiding the team technically. Experience preparing technical design documents, HLD/LLDs, and architecture diagrams.Familiarity with code quality tools (e.g., SonarQube, pylint), and version control workflows (Git).
Demonstrates strong verbal and written communication, proactive stakeholder engagement, and a collaborative attitude in cross-functional teams.Ability to articulate technical concepts clearly to both technical and business audiences.Experience in working with product owners, QA, and business analysts to translate requirements into deliverables.
Soft skills/other skills - To be Evaluated by Hiring Manager (To define how this will be evaluated)
Communication Skills
Communicate effectively with internal and customer stakeholders
Communication approach: verbal, emails and instant messages
Interpersonal Skills
Strong interpersonal skills to build and maintain productive relationships with team members
Provide constructive feedback during code reviews and be open to receiving feedback on your own code.
Problem-Solving And Analytical Thinking
Capability to troubleshoot and resolve issues efficiently.
Analytical mindset.
Task/ Work Updates
Prior experience in working on Agile/Scrum projects with exposure to tools like Jira/Azure DevOps.
Provides regular updates, proactive and due diligent to carry out responsibilities.
What Success Looks Like (6 12 Months) -
Expected Outcome
We are seeking a highly skilled Data Engineering specialist with above mentioned mentioned Primary Skills to join our dynamic team who are at the forefront of enabling enterprises in Healthcare sectors.
The ideal candidate should be passionate about working on Data Engineering on Azure cloud with strong focus on DevOps practices in building product for our customers.
Effectively Communicate and Collaborate with internal teams and customer to build code leveraging or building low level design documents aligning to standard coding principles and guidelines.
Secondary Skills (Good to have)
Good to have Azure Entra/AD skills and GitHub Actions.
Good to have orchestration experience using Airflow, Dagster, LogicApp.
Good to have expereince working on event-driven architectures using Kafka, Azure Event Hub.
Good to have exposure on Google Cloud Pub/Sub.
Good to have experience developing and maintaining Change Data Capture (CDC) solutions preferrably using Debezium.
Good to have hands-on experience on data migration projects specifically involving Azure Synapse and Databricks Lakehouse.
Good to have eperienced in managing cloud storage solutions on Azure Data Lake Storage . Experience with Google Cloud Storage will be an advantage.
Why Join Us - New Addition
Join a team driving modern Azure Data Engineering and Lakehouse transformation using Databricks, PySpark, ADF, and cloud-native technologies.
This Role Offers
Opportunity to work on enterprise-scale Azure data platforms
Hands-on exposure to Databricks, PySpark, ADF, and Lakehouse architecture
Ownership of solution design and technical decisions
Opportunity to lead, mentor, innovate, and drive engineering best practices