22 Data Integration jobs in Delhi

Job Title: Data Integration & Modeling Specialist

Job Type: Contract

Location: Remote

Duration: 6 Months

Job Summary:

We are seeking a highly skilled Data Integration & Modeling Specialist with hands-on experience in developing common metamodels, defining integration specifications, and working with semantic web technologies and various data formats. The ideal candidate will bring deep technical expertise and a collaborative mindset to support enterprise-level data integration and standardization initiatives.

Key Responsibilities:

Develop common metamodels by integrating requirements across diverse systems and organizations.

Define integration specifications, establish data standards, and develop logical and physical data models.

Collaborate with stakeholders to align data architectures with organizational needs and industry best practices.

Implement and govern semantic data solutions using RDF and SPARQL.

Perform data transformations and scripting using TCL, Python, and Java.

Work with multiple data formats including FRL, VRL, HRL, XML, and JSON to support integration and processing pipelines.

Document technical specifications and provide guidance on data standards and modeling best practices.

Required Qualifications:

3+ years of experience (within the last 8 years) in developing common metamodels, preferably using NIEM standards.

3+ years of experience (within the last 8 years) in:

Defining integration specifications

Developing data models

Governing data standards

2+ years of recent experience with:

Tool Command Language (TCL)

Python

Java

2+ years of experience with:

Resource Description Framework (RDF)

SPARQL Query Language

2+ years of experience working with:

Fixed Record Layout (FRL)

Variable Record Layout (VRL)

Hierarchical Record Layout (HRL)

XML

JSONodeling Specialist

About the Role:

We are seeking an experienced Data Architect to lead the transformation of enterprise data

solutions, with a strong focus on migrating Alteryx workflows into Azure Databricks. The

ideal candidate will have deep expertise in the Microsoft Azure ecosystem, including Azure

Data Factory, Databricks, Synapse Analytics, Microsoft Fabric, and a strong

background in data architecture, governance, and distributed computing. This role

requires both strategic thinking and hands-on architectural leadership to ensure scalable,

secure, and high-performance data solutions.

Key Responsibilities:

Define the overall migration strategy for transforming Alteryx workflows into

scalable, cloud-native data solutions on Azure Databricks.

Architect end-to-end data frameworks leveraging Databricks, Delta Lake, Azure

Data Lake, and Synapse.

Establish best practices, standards, and governance frameworks for pipeline

design, orchestration, and data lifecycle management.

Guide engineering teams in re-engineering Alteryx workflows into distributed Spark-

based architectures.

Collaborate with business stakeholders to ensure solutions align with analytics,

reporting, and advanced AI/ML initiatives.

Oversee data quality, lineage, and security compliance across the data

ecosystem.

Drive CI/CD adoption, automation, and DevOps practices for Azure Databricks

and related services.

Provide architectural leadership, design reviews, and mentorship to engineering

and analytics teams.

Optimize solutions for performance, scalability, and cost-efficiency within Azure.

Participate in enterprise architecture forums and influence data strategy across the

organization.

Required Skills and Qualifications:

10+ years of experience in data architecture, engineering, or solution design.

Proven expertise in Alteryx workflows and their modernization into Azure

Databricks (Spark, PySpark, SQL, Delta Lake).

Deep knowledge of the Microsoft Azure data ecosystem:

o Azure Data Factory (ADF)

o Azure Synapse Analytics

o Microsoft Fabric

o Azure Databricks

Strong background in data governance, lineage, security, and compliance

frameworks.

Demonstrated experience in architecting data lakes, data warehouses, and

analytics platforms.

Proficiency in Python, SQL, and Apache Spark for prototyping and design

validation.

Excellent leadership, communication, and stakeholder management skills.

Preferred Qualifications:

Microsoft Azure certifications (e.g., Azure Solutions Architect Expert, Azure Data

Engineer Associate).

Experience leading large-scale migration programs or modernization initiatives.

Familiarity with enterprise architecture frameworks (TOGAF, Zachman).

Exposure to machine learning enablement on Azure Databricks.

Strong understanding of Agile delivery and working in multi-disciplinary teams.

About the Role:

We are seeking an experienced Data Architect to lead the transformation of enterprise data

solutions, with a strong focus on migrating Alteryx workflows into Azure Databricks. The

ideal candidate will have deep expertise in the Microsoft Azure ecosystem, including Azure

Data Factory, Databricks, Synapse Analytics, Microsoft Fabric, and a strong

background in data architecture, governance, and distributed computing. This role

requires both strategic thinking and hands-on architectural leadership to ensure scalable,

secure, and high-performance data solutions.

Key Responsibilities:

Define the overall migration strategy for transforming Alteryx workflows into

scalable, cloud-native data solutions on Azure Databricks.

Architect end-to-end data frameworks leveraging Databricks, Delta Lake, Azure

Data Lake, and Synapse.

Establish best practices, standards, and governance frameworks for pipeline

design, orchestration, and data lifecycle management.

Guide engineering teams in re-engineering Alteryx workflows into distributed Spark-

based architectures.

Collaborate with business stakeholders to ensure solutions align with analytics,

reporting, and advanced AI/ML initiatives.

Oversee data quality, lineage, and security compliance across the data

ecosystem.

Drive CI/CD adoption, automation, and DevOps practices for Azure Databricks

and related services.

Provide architectural leadership, design reviews, and mentorship to engineering

and analytics teams.

Optimize solutions for performance, scalability, and cost-efficiency within Azure.

Participate in enterprise architecture forums and influence data strategy across the

organization.

Required Skills and Qualifications:

10+ years of experience in data architecture, engineering, or solution design.

Proven expertise in Alteryx workflows and their modernization into Azure

Databricks (Spark, PySpark, SQL, Delta Lake).

Deep knowledge of the Microsoft Azure data ecosystem:

o Azure Data Factory (ADF)

o Azure Synapse Analytics

o Microsoft Fabric

o Azure Databricks

Strong background in data governance, lineage, security, and compliance

frameworks.

Demonstrated experience in architecting data lakes, data warehouses, and

analytics platforms.

Proficiency in Python, SQL, and Apache Spark for prototyping and design

validation.

Excellent leadership, communication, and stakeholder management skills.

Preferred Qualifications:

Microsoft Azure certifications (e.g., Azure Solutions Architect Expert, Azure Data

Engineer Associate).

Experience leading large-scale migration programs or modernization initiatives.

Familiarity with enterprise architecture frameworks (TOGAF, Zachman).

Exposure to machine learning enablement on Azure Databricks.

Strong understanding of Agile delivery and working in multi-disciplinary teams.

About the Role:

We are seeking an experienced Data Architect to lead the transformation of enterprise data

solutions, with a strong focus on migrating Alteryx workflows into Azure Databricks. The

ideal candidate will have deep expertise in the Microsoft Azure ecosystem, including Azure

Data Factory, Databricks, Synapse Analytics, Microsoft Fabric, and a strong

background in data architecture, governance, and distributed computing. This role

requires both strategic thinking and hands-on architectural leadership to ensure scalable,

secure, and high-performance data solutions.

Key Responsibilities:

Define the overall migration strategy for transforming Alteryx workflows into

scalable, cloud-native data solutions on Azure Databricks.

Architect end-to-end data frameworks leveraging Databricks, Delta Lake, Azure

Data Lake, and Synapse.

Establish best practices, standards, and governance frameworks for pipeline

design, orchestration, and data lifecycle management.

Guide engineering teams in re-engineering Alteryx workflows into distributed Spark-

based architectures.

Collaborate with business stakeholders to ensure solutions align with analytics,

reporting, and advanced AI/ML initiatives.

Oversee data quality, lineage, and security compliance across the data

ecosystem.

Drive CI/CD adoption, automation, and DevOps practices for Azure Databricks

and related services.

Provide architectural leadership, design reviews, and mentorship to engineering

and analytics teams.

Optimize solutions for performance, scalability, and cost-efficiency within Azure.

Participate in enterprise architecture forums and influence data strategy across the

organization.

Required Skills and Qualifications:

10+ years of experience in data architecture, engineering, or solution design.

Proven expertise in Alteryx workflows and their modernization into Azure

Databricks (Spark, PySpark, SQL, Delta Lake).

Deep knowledge of the Microsoft Azure data ecosystem:

o Azure Data Factory (ADF)

o Azure Synapse Analytics

o Microsoft Fabric

o Azure Databricks

Strong background in data governance, lineage, security, and compliance

frameworks.

Demonstrated experience in architecting data lakes, data warehouses, and

analytics platforms.

Proficiency in Python, SQL, and Apache Spark for prototyping and design

validation.

Excellent leadership, communication, and stakeholder management skills.

Preferred Qualifications:

Microsoft Azure certifications (e.g., Azure Solutions Architect Expert, Azure Data

Engineer Associate).

Experience leading large-scale migration programs or modernization initiatives.

Familiarity with enterprise architecture frameworks (TOGAF, Zachman).

Exposure to machine learning enablement on Azure Databricks.

Strong understanding of Agile delivery and working in multi-disciplinary teams.

Job Title: Senior Manager - Data Engineering Lead

Qualification: Bachelor’s or master’s degree in computer science, Data Engineering, or related field.

Required skillset:

• Experience in data engineering.
• Proven experience in cloud platforms (AWS, Azure, or GCP) and data services (Glue, Synapse, Big Query, Databricks, etc.).
• Hands-on experience with tools like Apache Spark, Kafka, Airflow, dbt, and modern orchestration platforms.
• Technical Skills
• Proficient in SQL, Python/Scala/Java.
• Strong understanding of modern data Lake concepts (e.g., Snowflake, Redshift, BigQuery).
• Familiarity with CI/CD, Infrastructure as Code (e.g., Terraform), and DevOps for data.

Nice to Have:

• Prior experience working in a regulated industry (alcohol, pharma, tobacco, etc.).
• Exposure to demand forecasting, route-to-market analytics, or distributor performance management.
• Knowledge of CRM, ERP, or supply chain systems (e.g., Salesforce, SAP, Oracle).
• Familiarity with marketing attribution models and campaign performance tracking.

Preferred Attributes:

• Strong analytical and problem-solving skills.
• Excellent communication and stakeholder engagement abilities.
• Passion for data-driven innovation and delivering business impact.
• Certification in cloud platforms or data engineering (e.g., Google Cloud Professional Data Engineer).
• Excellent communication and stakeholder management skills.

Key Accountabilities:

• Design and implement scalable, high-performance data architecture solutions aligned with enterprise strategy.
• Define standards and best practices for data modelling, metadata management, and data governance.
• Collaborate with business stakeholders, data scientists, and application architects to align data infrastructure with business needs.
• Guide the selection of technologies, including cloud-native and hybrid data architecture patterns (e.g., Lambda/Kappa architectures).
• Lead the development, deployment, and maintenance of end-to-end data pipelines using ETL/ELT frameworks.
• Manage ingestion from structured and unstructured data sources (APIs, files, databases, streaming sources).
• Optimize data workflows for performance, reliability, and cost efficiency.
• Ensure data quality, lineage, cataloging, and security through automated validation and monitoring.

• Oversee data lake design, implementation, and daily operations (e.g., Azure Data Lake, AWS S3, GCP BigLake).
• Implement access controls, data lifecycle management, and partitioning strategies.
• Monitor and manage performance, storage costs, and data availability in real time.
• Ensure compliance with enterprise data policies and regulatory requirements (e.g., GDPR, CCPA).

• Lead and mentor a team of data engineers and architects.
• Establish a culture of continuous improvement, innovation, and operational excellence.
• Work closely with IT, DevOps, and InfoSec teams to ensure secure and scalable infrastructure.

Flexible Working Statement: Flexibility is key to our success. From part-time and compressed hours to different locations, our people work flexibly in ways to suit them. Talk to us about what flexibility means to you so that you’re supported from day one.

Diversity statement: Our purpose is to celebrate life, every day, everywhere. And creating an inclusive culture, where everyone feels valued and that they can belong, is a crucial part of this.

We embrace diversity in the broadest possible sense. This means that you’ll be welcomed and celebrated for who you are just by being you. You’ll be part of and help build and champion an inclusive culture that celebrates people of different gender, ethnicity, ability, age, sexual orientation, social class, educational backgrounds, experiences, mindsets, and more.

Our ambition is to create the best performing, most trusted and respected consumer products companies in the world. Join us and help transform our business as we take our brands to the next level and build new ones as part of shaping the next generation of celebrations for consumers around the world.

Job Title: Senior Manager - Data Engineering Lead

Qualification: Bachelor’s or master’s degree in computer science, Data Engineering, or related field.

Required skillset:

• Experience in data engineering.
• Proven experience in cloud platforms (AWS, Azure, or GCP) and data services (Glue, Synapse, Big Query, Databricks, etc.).
• Hands-on experience with tools like Apache Spark, Kafka, Airflow, dbt, and modern orchestration platforms.
• Technical Skills
• Proficient in SQL, Python/Scala/Java.
• Strong understanding of modern data Lake concepts (e.g., Snowflake, Redshift, BigQuery).
• Familiarity with CI/CD, Infrastructure as Code (e.g., Terraform), and DevOps for data.

Nice to Have:

• Prior experience working in a regulated industry (alcohol, pharma, tobacco, etc.).
• Exposure to demand forecasting, route-to-market analytics, or distributor performance management.
• Knowledge of CRM, ERP, or supply chain systems (e.g., Salesforce, SAP, Oracle).
• Familiarity with marketing attribution models and campaign performance tracking.

Preferred Attributes:

• Strong analytical and problem-solving skills.
• Excellent communication and stakeholder engagement abilities.
• Passion for data-driven innovation and delivering business impact.
• Certification in cloud platforms or data engineering (e.g., Google Cloud Professional Data Engineer).
• Excellent communication and stakeholder management skills.

Key Accountabilities:

• Design and implement scalable, high-performance data architecture solutions aligned with enterprise strategy.
• Define standards and best practices for data modelling, metadata management, and data governance.
• Collaborate with business stakeholders, data scientists, and application architects to align data infrastructure with business needs.
• Guide the selection of technologies, including cloud-native and hybrid data architecture patterns (e.g., Lambda/Kappa architectures).
• Lead the development, deployment, and maintenance of end-to-end data pipelines using ETL/ELT frameworks.
• Manage ingestion from structured and unstructured data sources (APIs, files, databases, streaming sources).
• Optimize data workflows for performance, reliability, and cost efficiency.
• Ensure data quality, lineage, cataloging, and security through automated validation and monitoring.

• Oversee data lake design, implementation, and daily operations (e.g., Azure Data Lake, AWS S3, GCP BigLake).
• Implement access controls, data lifecycle management, and partitioning strategies.
• Monitor and manage performance, storage costs, and data availability in real time.
• Ensure compliance with enterprise data policies and regulatory requirements (e.g., GDPR, CCPA).

• Lead and mentor a team of data engineers and architects.
• Establish a culture of continuous improvement, innovation, and operational excellence.
• Work closely with IT, DevOps, and InfoSec teams to ensure secure and scalable infrastructure.

Flexible Working Statement: Flexibility is key to our success. From part-time and compressed hours to different locations, our people work flexibly in ways to suit them. Talk to us about what flexibility means to you so that you’re supported from day one.

Diversity statement: Our purpose is to celebrate life, every day, everywhere. And creating an inclusive culture, where everyone feels valued and that they can belong, is a crucial part of this.

We embrace diversity in the broadest possible sense. This means that you’ll be welcomed and celebrated for who you are just by being you. You’ll be part of and help build and champion an inclusive culture that celebrates people of different gender, ethnicity, ability, age, sexual orientation, social class, educational backgrounds, experiences, mindsets, and more.

Our ambition is to create the best performing, most trusted and respected consumer products companies in the world. Join us and help transform our business as we take our brands to the next level and build new ones as part of shaping the next generation of celebrations for consumers around the world.

Job Title: Senior Manager - Data Engineering Lead

Qualification: Bachelor’s or master’s degree in computer science, Data Engineering, or related field.

Required skillset:

• Experience in data engineering.
• Proven experience in cloud platforms (AWS, Azure, or GCP) and data services (Glue, Synapse, Big Query, Databricks, etc.).
• Hands-on experience with tools like Apache Spark, Kafka, Airflow, dbt, and modern orchestration platforms.
• Technical Skills
• Proficient in SQL, Python/Scala/Java.
• Strong understanding of modern data Lake concepts (e.g., Snowflake, Redshift, BigQuery).
• Familiarity with CI/CD, Infrastructure as Code (e.g., Terraform), and DevOps for data.

Nice to Have:

• Prior experience working in a regulated industry (alcohol, pharma, tobacco, etc.).
• Exposure to demand forecasting, route-to-market analytics, or distributor performance management.
• Knowledge of CRM, ERP, or supply chain systems (e.g., Salesforce, SAP, Oracle).
• Familiarity with marketing attribution models and campaign performance tracking.

Preferred Attributes:

• Strong analytical and problem-solving skills.
• Excellent communication and stakeholder engagement abilities.
• Passion for data-driven innovation and delivering business impact.
• Certification in cloud platforms or data engineering (e.g., Google Cloud Professional Data Engineer).
• Excellent communication and stakeholder management skills.

Key Accountabilities:

• Design and implement scalable, high-performance data architecture solutions aligned with enterprise strategy.
• Define standards and best practices for data modelling, metadata management, and data governance.
• Collaborate with business stakeholders, data scientists, and application architects to align data infrastructure with business needs.
• Guide the selection of technologies, including cloud-native and hybrid data architecture patterns (e.g., Lambda/Kappa architectures).
• Lead the development, deployment, and maintenance of end-to-end data pipelines using ETL/ELT frameworks.
• Manage ingestion from structured and unstructured data sources (APIs, files, databases, streaming sources).
• Optimize data workflows for performance, reliability, and cost efficiency.
• Ensure data quality, lineage, cataloging, and security through automated validation and monitoring.

• Oversee data lake design, implementation, and daily operations (e.g., Azure Data Lake, AWS S3, GCP BigLake).
• Implement access controls, data lifecycle management, and partitioning strategies.
• Monitor and manage performance, storage costs, and data availability in real time.
• Ensure compliance with enterprise data policies and regulatory requirements (e.g., GDPR, CCPA).

• Lead and mentor a team of data engineers and architects.
• Establish a culture of continuous improvement, innovation, and operational excellence.
• Work closely with IT, DevOps, and InfoSec teams to ensure secure and scalable infrastructure.

Flexible Working Statement: Flexibility is key to our success. From part-time and compressed hours to different locations, our people work flexibly in ways to suit them. Talk to us about what flexibility means to you so that you’re supported from day one.

Diversity statement: Our purpose is to celebrate life, every day, everywhere. And creating an inclusive culture, where everyone feels valued and that they can belong, is a crucial part of this.

We embrace diversity in the broadest possible sense. This means that you’ll be welcomed and celebrated for who you are just by being you. You’ll be part of and help build and champion an inclusive culture that celebrates people of different gender, ethnicity, ability, age, sexual orientation, social class, educational backgrounds, experiences, mindsets, and more.

Our ambition is to create the best performing, most trusted and respected consumer products companies in the world. Join us and help transform our business as we take our brands to the next level and build new ones as part of shaping the next generation of celebrations for consumers around the world.