Zorba is the new age analytics provider that brings data driven decision to life for its clients. We believe in getting analytics executed on ground with the client team rather than just creating complex machine learning or predictive modelling algorithms. 

We offer services across the spectrum ranging from analytics training and setting up data centres to delivering analytics based strategic consulting solutions. One of the key value adds we do is with the speed at which we deliver solutions.

Headquartered in Mumbai, Zorba was conceived with an objective of creating value for businesses in near future rather than long term. We are experts in leveraging big data, building data driven solutions and operationalizing analytics at each stage of decision making process with following key offerings: 

•	Data Visualization and Dashboard design
•	Predictive Modelling Algorithms
•	Data Management and Transformation
•	Analytics based reporting solutions
•	Marketing and Business Process Optimization

Witnessing the stories of success and failure of numerous businesses at different stages, we came to the conclusion that every business can be successful if improvisation continues relentlessly. 

We want to make this process faster and smarter for our clients in their quest for growth by hand holding through data analytics and strategic leadership for effective decision making. 

You can follow us on :
https://www.quora.com/profile/Yash-Chaudhary-516
https://www.instagram.com/zorbaconsulting/?hl=en
https://twitter.com/ConsultingZorba
https://www.facebook.com/Zorbaconsulting/

Zorba Consulting India

Data Engineer (Spark/Scala)
&nbsp;
About the Role
We are seeking an experienced&nbsp;Data Engineer&nbsp;to design, build, and optimize complex data workflows across on-premises and cloud environments. This role requires deep hands-on expertise in&nbsp;Apache Spark, Databricks, and Scala/PySpark, along with strong SQL and Python skills, to build robust, high-performance data pipelines. You will work extensively on&nbsp;complex on-prem workflows, integrating data across multiple file systems and formats, migrating and modernizing legacy processes, and ensuring efficient, reliable data movement across heterogeneous environments.
 Key Responsibilities
<ul>
<li>
Design, develop, and maintain large-scale data pipelines using&nbsp;Apache Spark,&nbsp;Databricks,&nbsp;Scala Spark, and&nbsp;PySpark
</li>
<li>
Build and support&nbsp;complex on-premises data workflows, including migration/hybrid on-prem-to-cloud integration patterns
</li>
<li>
Integrate data across diverse&nbsp;file systems&nbsp;(on-prem file shares, NAS, HDFS, S3) and formats&nbsp;JSON, Parquet, Fixed-Length, CSV, Excel, Avro
</li>
<li>
Write efficient, optimized&nbsp;SQL&nbsp;for data extraction, transformation, and loading across relational databases
</li>
<li>
Connect to and extract data efficiently from various source&nbsp;databases, tuning queries and pipelines for performance at scale
</li>
<li>
Develop and maintain workflow orchestration using&nbsp;Airflow&nbsp;(or similar schedulers) for reliable, monitored pipeline execution
</li>
<li>
Write clean, production-grade&nbsp;Python&nbsp;code for data processing, automation, and tooling
</li>
<li>
Build and maintain&nbsp;unit/integration tests&nbsp;for data pipelines to ensure data quality and reliability
</li>
<li>
Create and maintain clear&nbsp;technical documentation&nbsp;for pipelines, data flows, and system architecture
</li>
<li>
Troubleshoot and resolve data pipeline failures, performance bottlenecks, and data quality issues in complex, multi-system workflows
</li>
<li>
Collaborate with cross-functional teams (data science, analytics, application engineering) to support downstream data consumption
</li>
<li>
Support cloud integration efforts, particularly with&nbsp;Azure, as workloads evolve from on-prem to hybrid/cloud architectures
</li>
</ul>
&nbsp;
Required Qualifications
Primary Skills:
<ul>
<li>
Strong hands-on experience with&nbsp;Apache Spark&nbsp;and&nbsp;Databricks&nbsp;for large-scale data processing
</li>
<li>
Proficiency with&nbsp;Amazon S3&nbsp;for data storage and pipeline integration
</li>
<li>
Strong&nbsp;SQL skills - query optimization, complex joins, performance tuning
</li>
<li>
Proven experience integrating data across&nbsp;various file systems&nbsp;and formats:&nbsp;JSON, Parquet, Fixed-Length, CSV, Excel, Avro, etc.
</li>
<li>
Strong knowledge of&nbsp;Scala Spark&nbsp;and&nbsp;PySpark&nbsp;for distributed data processing
</li>
<li>
Strong&nbsp;Python&nbsp;programming skills for scripting, automation, and data engineering tasks
</li>
<li>
Strong experience connecting to and&nbsp;efficiently extracting data from databases&nbsp;(relational/other), including performance-conscious extraction strategies
</li>
<li>
Demonstrated experience working on&nbsp;complex on-prem data workflows&nbsp;(multi-system integration, legacy system data extraction, hybrid on-prem/cloud pipelines)
</li>
<li>
Experience leveraging coding assistant tools and implementing AI agents to enhance development productivity and task execution.
</li>
</ul>
 
Secondary Skills:
<ul>
<li>
Experience with&nbsp;Azure&nbsp;cloud services (storage, compute, data services)
</li>
<li>
Experience with&nbsp;Apache Airflow&nbsp;for workflow orchestration and scheduling
</li>
<li>
Experience writing&nbsp;automated tests&nbsp;for data pipelines (unit, integration, data quality checks)
</li>
<li>
Strong&nbsp;documentation&nbsp;skills able to clearly document pipelines, data lineage, and technical designs
</li>
</ul>
 
Good to Have:
<ul>
<li>
Working knowledge of&nbsp;Java
</li>
<li>
Familiarity with&nbsp;React&nbsp;for building internal tooling/dashboards
</li>
<li>
Experience with&nbsp;Prefect&nbsp;for workflow orchestration
</li>
<li>
PBM (Pharmacy Benefit Management) / Healthcare domain knowledge
Data Engineer (Spark/Scala)
&nbsp;
About the Role
We are seeking an experienced&nbsp;Data Engineer&nbsp;to design, build, and optimize complex data workflows across on-premises and cloud environments. This role requires deep hands-on expertise in&nbsp;Apache Spark, Databricks, and Scala/PySpark, along with strong SQL and Python skills, to build robust, high-performance data pipelines. You will work extensively on&nbsp;complex on-prem workflows, integrating data across multiple file systems and formats, migrating and modernizing legacy processes, and ensuring efficient, reliable data movement across heterogeneous environments.
 Key Responsibilities
<ul>
<li>
Design, develop, and maintain large-scale data pipelines using&nbsp;Apache Spark,&nbsp;Databricks,&nbsp;Scala Spark, and&nbsp;PySpark
</li>
<li>
Build and support&nbsp;complex on-premises data workflows, including migration/hybrid on-prem-to-cloud integration patterns
</li>
<li>
Integrate data across diverse&nbsp;file systems&nbsp;(on-prem file shares, NAS, HDFS, S3) and formats&nbsp;JSON, Parquet, Fixed-Length, CSV, Excel, Avro
</li>
<li>
Write efficient, optimized&nbsp;SQL&nbsp;for data extraction, transformation, and loading across relational databases
</li>
<li>
Connect to and extract data efficiently from various source&nbsp;databases, tuning queries and pipelines for performance at scale
</li>
<li>
Develop and maintain workflow orchestration using&nbsp;Airflow&nbsp;(or similar schedulers) for reliable, monitored pipeline execution
</li>
<li>
Write clean, production-grade&nbsp;Python&nbsp;code for data processing, automation, and tooling
</li>
<li>
Build and maintain&nbsp;unit/integration tests&nbsp;for data pipelines to ensure data quality and reliability
</li>
<li>
Create and maintain clear&nbsp;technical documentation&nbsp;for pipelines, data flows, and system architecture
</li>
<li>
Troubleshoot and resolve data pipeline failures, performance bottlenecks, and data quality issues in complex, multi-system workflows
</li>
<li>
Collaborate with cross-functional teams (data science, analytics, application engineering) to support downstream data consumption
</li>
<li>
Support cloud integration efforts, particularly with&nbsp;Azure, as workloads evolve from on-prem to hybrid/cloud architectures
</li>
</ul>
&nbsp;
Required Qualifications
Primary Skills:
<ul>
<li>
Strong hands-on experience with&nbsp;Apache Spark&nbsp;and&nbsp;Databricks&nbsp;for large-scale data processing
</li>
<li>
Proficiency with&nbsp;Amazon S3&nbsp;for data storage and pipeline integration
</li>
<li>
Strong&nbsp;SQL skills - query optimization, complex joins, performance tuning
</li>
<li>
Proven experience integrating data across&nbsp;various file systems&nbsp;and formats:&nbsp;JSON, Parquet, Fixed-Length, CSV, Excel, Avro, etc.
</li>
<li>
Strong knowledge of&nbsp;Scala Spark&nbsp;and&nbsp;PySpark&nbsp;for distributed data processing
</li>
<li>
Strong&nbsp;Python&nbsp;programming skills for scripting, automation, and data engineering tasks
</li>
<li>
Strong experience connecting to and&nbsp;efficiently extracting data from databases&nbsp;(relational/other), including performance-conscious extraction strategies
</li>
<li>
Demonstrated experience working on&nbsp;complex on-prem data workflows&nbsp;(multi-system integration, legacy system data extraction, hybrid on-prem/cloud pipelines)
</li>
<li>
Experience leveraging coding assistant tools and implementing AI agents to enhance development productivity and task execution.
</li>
</ul>
 
Secondary Skills:
<ul>
<li>
Experience with&nbsp;Azure&nbsp;cloud services (storage, compute, data services)
</li>
<li>
Experience with&nbsp;Apache Airflow&nbsp;for workflow orchestration and scheduling
</li>
<li>
Experience writing&nbsp;automated tests&nbsp;for data pipelines (unit, integration, data quality checks)
</li>
<li>
Strong&nbsp;documentation&nbsp;skills able to clearly document pipelines, data lineage, and technical designs
</li>
</ul>
 
Good to Have:
<ul>
<li>
Working knowledge of&nbsp;Java
</li>
<li>
Familiarity with&nbsp;React&nbsp;for building internal tooling/dashboards
</li>
<li>
Experience with&nbsp;Prefect&nbsp;for workflow orchestration
</li>
<li>
PBM (Pharmacy Benefit Management) / Healthcare domain knowledge.
Data Engineer (Spark/Scala)
&nbsp;
About the Role
We are seeking an experienced&nbsp;Data Engineer&nbsp;to design, build, and optimize complex data workflows across on-premises and cloud environments. This role requires deep hands-on expertise in&nbsp;Apache Spark, Databricks, and Scala/PySpark, along with strong SQL and Python skills, to build robust, high-performance data pipelines. You will work extensively on&nbsp;complex on-prem workflows, integrating data across multiple file systems and formats, migrating and modernizing legacy processes, and ensuring efficient, reliable data movement across heterogeneous environments.
 Key Responsibilities
<ul>
<li>
Design, develop, and maintain large-scale data pipelines using&nbsp;Apache Spark,&nbsp;Databricks,&nbsp;Scala Spark, and&nbsp;PySpark
</li>
<li>
Build and support&nbsp;complex on-premises data workflows, including migration/hybrid on-prem-to-cloud integration patterns
</li>
<li>
Integrate data across diverse&nbsp;file systems&nbsp;(on-prem file shares, NAS, HDFS, S3) and formats&nbsp;JSON, Parquet, Fixed-Length, CSV, Excel, Avro
</li>
<li>
Write efficient, optimized&nbsp;SQL&nbsp;for data extraction, transformation, and loading across relational databases
</li>
<li>
Connect to and extract data efficiently from various source&nbsp;databases, tuning queries and pipelines for performance at scale
</li>
<li>
Develop and maintain workflow orchestration using&nbsp;Airflow&nbsp;(or similar schedulers) for reliable, monitored pipeline execution
</li>
<li>
Write clean, production-grade&nbsp;Python&nbsp;code for data processing, automation, and tooling
</li>
<li>
Build and maintain&nbsp;unit/integration tests&nbsp;for data pipelines to ensure data quality and reliability
</li>
<li>
Create and maintain clear&nbsp;technical documentation&nbsp;for pipelines, data flows, and system architecture
</li>
<li>
Troubleshoot and resolve data pipeline failures, performance bottlenecks, and data quality issues in complex, multi-system workflows
</li>
<li>
Collaborate with cross-functional teams (data science, analytics, application engineering) to support downstream data consumption
</li>
<li>
Support cloud integration efforts, particularly with&nbsp;Azure, as workloads evolve from on-prem to hybrid/cloud architectures
</li>
</ul>
&nbsp;
Required Qualifications
Primary Skills:
<ul>
<li>
Strong hands-on experience with&nbsp;Apache Spark&nbsp;and&nbsp;Databricks&nbsp;for large-scale data processing
</li>
<li>
Proficiency with&nbsp;Amazon S3&nbsp;for data storage and pipeline integration
</li>
<li>
Strong&nbsp;SQL skills - query optimization, complex joins, performance tuning
</li>
<li>
Proven experience integrating data across&nbsp;various file systems&nbsp;and formats:&nbsp;JSON, Parquet, Fixed-Length, CSV, Excel, Avro, etc.
</li>
<li>
Strong knowledge of&nbsp;Scala Spark&nbsp;and&nbsp;PySpark&nbsp;for distributed data processing
</li>
<li>
Strong&nbsp;Python&nbsp;programming skills for scripting, automation, and data engineering tasks
</li>
<li>
Strong experience connecting to and&nbsp;efficiently extracting data from databases&nbsp;(relational/other), including performance-conscious extraction strategies
</li>
<li>
Demonstrated experience working on&nbsp;complex on-prem data workflows&nbsp;(multi-system integration, legacy system data extraction, hybrid on-prem/cloud pipelines)
</li>
<li>
Experience leveraging coding assistant tools and implementing AI agents to enhance development productivity and task execution.
</li>
</ul>
 
Secondary Skills:
<ul>
<li>
Experience with&nbsp;Azure&nbsp;cloud services (storage, compute, data services)
</li>
<li>
Experience with&nbsp;Apache Airflow&nbsp;for workflow orchestration and scheduling
</li>
<li>
Experience writing&nbsp;automated tests&nbsp;for data pipelines (unit, integration, data quality checks)
</li>
<li>
Strong&nbsp;documentation&nbsp;skills able to clearly document pipelines, data lineage, and technical designs
</li>
</ul>
 
Good to Have:
<ul>
<li>
Working knowledge of&nbsp;Java
</li>
<li>
Familiarity with&nbsp;React&nbsp;for building internal tooling/dashboards
</li>
<li>
Experience with&nbsp;Prefect&nbsp;for workflow orchestration
</li>
<li>
PBM (Pharmacy Benefit Management) / Healthcare domain knowledge
Data Engineer (Spark/Scala)
&nbsp;
About the Role
We are seeking an experienced&nbsp;Data Engineer&nbsp;to design, build, and optimize complex data workflows across on-premises and cloud environments. This role requires deep hands-on expertise in&nbsp;Apache Spark, Databricks, and Scala/PySpark, along with strong SQL and Python skills, to build robust, high-performance data pipelines. You will work extensively on&nbsp;complex on-prem workflows, integrating data across multiple file systems and formats, migrating and modernizing legacy processes, and ensuring efficient, reliable data movement across heterogeneous environments.
 Key Responsibilities
<ul>
<li>
Design, develop, and maintain large-scale data pipelines using&nbsp;Apache Spark,&nbsp;Databricks,&nbsp;Scala Spark, and&nbsp;PySpark
</li>
<li>
Build and support&nbsp;complex on-premises data workflows, including migration/hybrid on-prem-to-cloud integration patterns
</li>
<li>
Integrate data across diverse&nbsp;file systems&nbsp;(on-prem file shares, NAS, HDFS, S3) and formats&nbsp;JSON, Parquet, Fixed-Length, CSV, Excel, Avro
</li>
<li>
Write efficient, optimized&nbsp;SQL&nbsp;for data extraction, transformation, and loading across relational databases
</li>
<li>
Connect to and extract data efficiently from various source&nbsp;databases, tuning queries and pipelines for performance at scale
</li>
<li>
Develop and maintain workflow orchestration using&nbsp;Airflow&nbsp;(or similar schedulers) for reliable, monitored pipeline execution
</li>
<li>
Write clean, production-grade&nbsp;Python&nbsp;code for data processing, automation, and tooling
</li>
<li>
Build and maintain&nbsp;unit/integration tests&nbsp;for data pipelines to ensure data quality and reliability
</li>
<li>
Create and maintain clear&nbsp;technical documentation&nbsp;for pipelines, data flows, and system architecture
</li>
<li>
Troubleshoot and resolve data pipeline failures, performance bottlenecks, and data quality issues in complex, multi-system workflows
</li>
<li>
Collaborate with cross-functional teams (data science, analytics, application engineering) to support downstream data consumption
</li>
<li>
Support cloud integration efforts, particularly with&nbsp;Azure, as workloads evolve from on-prem to hybrid/cloud architectures
</li>
</ul>
&nbsp;
Required Qualifications
Primary Skills:
<ul>
<li>
Strong hands-on experience with&nbsp;Apache Spark&nbsp;and&nbsp;Databricks&nbsp;for large-scale data processing
</li>
<li>
Proficiency with&nbsp;Amazon S3&nbsp;for data storage and pipeline integration
</li>
<li>
Strong&nbsp;SQL skills - query optimization, complex joins, performance tuning
</li>
<li>
Proven experience integrating data across&nbsp;various file systems&nbsp;and formats:&nbsp;JSON, Parquet, Fixed-Length, CSV, Excel, Avro, etc.
</li>
<li>
Strong knowledge of&nbsp;Scala Spark&nbsp;and&nbsp;PySpark&nbsp;for distributed data processing
</li>
<li>
Strong&nbsp;Python&nbsp;programming skills for scripting, automation, and data engineering tasks
</li>
<li>
Strong experience connecting to and&nbsp;efficiently extracting data from databases&nbsp;(relational/other), including performance-conscious extraction strategies
</li>
<li>
Demonstrated experience working on&nbsp;complex on-prem data workflows&nbsp;(multi-system integration, legacy system data extraction, hybrid on-prem/cloud pipelines)
</li>
<li>
Experience leveraging coding assistant tools and implementing AI agents to enhance development productivity and task execution.
</li>
</ul>
 
Secondary Skills:
<ul>
<li>
Experience with&nbsp;Azure&nbsp;cloud services (storage, compute, data services)
</li>
<li>
Experience with&nbsp;Apache Airflow&nbsp;for workflow orchestration and scheduling
</li>
<li>
Experience writing&nbsp;automated tests&nbsp;for data pipelines (unit, integration, data quality checks)
</li>
<li>
Strong&nbsp;documentation&nbsp;skills able to clearly document pipelines, data lineage, and technical designs
</li>
</ul>
 
Good to Have:
<ul>
<li>
Working knowledge of&nbsp;Java
</li>
<li>
Familiarity with&nbsp;React&nbsp;for building internal tooling/dashboards
</li>
<li>
Experience with&nbsp;Prefect&nbsp;for workflow orchestration
</li>
<li>
PBM (Pharmacy Benefit Management) / Healthcare domain knowledge
</li>
</ul>
</li>
</ul>
</li>
</ul>
</li>
</ul>