Overview

About Kinaxis

Are you looking to join an innovative, market-leading company where you can truly elevate your career? At Kinaxis we are serious about culture, we are serious about technology, we are serious about customers, and we are serious about not taking ourselves too seriously. If you are looking to be part of an incredible growth story, then we might just be the place for you!

In 1984, we started out as a team of three engineers. Today, we have grown to become a global organization with over 2000 employees around the world, 6 global office and a best-in-class HQ in Ottawa, Canada. As winners of several Top Employer awards globally, we are proud to work with our customers and employees towards solving some of the biggest challenges facing supply chains today.

Kinaxis is a global leader in modern supply chain orchestration, powering complex global supply chains, and supporting the people who manage them. Our powerful, AI infused platform provides full transparency and visibility across end-to-end supply chains, enabling our customers to make faster, better decisions. We are trusted by renowned global brands to provide the agility and predictability needed to navigate today’s volatility and disruption.

With more than 40,000 users in over 100 countries, we are expanding our team as we continue to innovate and revolutionize how we support our customers.

Responsibilities

Location

Chennai, India

About the role & team

We are seeking a Senior Data Engineer to help scale Kinaxis’ Migrations and Data Integrations capabilities. This is a hands-on engineering role focused on building, migrating, maintaining, and supporting data assets and integrations that enable Kinaxis’ modernization journey.

You will help migrate pipelines, transformations, data models, orchestration workflows, observability/reporting dependencies, and related components from legacy platforms such as Snowflake, PostgreSQL, SQL Server, Airflow, Grafana, Informatica, and related tools into the modern Kinaxis stack built on Databricks, GCP, dbt, Power BI, and cloud-native orchestration and observability tooling.

You will also build new application-to-application connectors in MuleSoft, while maintaining, troubleshooting, enhancing, and selectively migrating existing integrations currently implemented in Informatica.

This role is ideal for an engineer who enjoys practical modernization work: rebuilding legacy assets in modern technologies, improving reliability and supportability, and creating reusable patterns that accelerate platform transition at scale.

Qualifications

Key responsibilities

Migrations and delivery

- - Build and migrate data pipelines, transformations, and models into the modern data platform using Databricks, GCP, dbt, Power BI, and related tooling.
- Refactor, rebuild, or migrate legacy data assets currently implemented in platforms such as Snowflake, PostgreSQL, SQL Server, Airflow, Grafana, Informatica, and similar systems.
- Develop reusable migration components, templates, validation checks, and automation assets that improve speed, consistency, and quality across modernization initiatives.
- Support validation, reconciliation, issue triage, testing, and cutover-readiness activities for migrated assets.
- Contribute to runbooks, technical documentation, and delivery standards that make the Migration Factory repeatable and scalable.

Data Integrations engineering

- - Build and maintain new application-to-application connectors in MuleSoft.
- Maintain, troubleshoot, and enhance existing integrations built in Informatica any Python, ensuring reliability and operational supportability.
- Migrate or refactor selected legacy Informatica integrations into modern integration patterns and platforms where appropriate.
- Implement integration logic using APIs, file-based interfaces, orchestration workflows, and batch or event-driven processing patterns.
- Develop validation, monitoring, reconciliation, and error-handling mechanisms to ensure production-ready integrations.

Engineering and operational excellence

- - Build and maintain robust, scalable, and efficient data pipelines for batch and streaming use cases.
- Implement data validation, cleansing, and error-handling mechanisms to maintain high data quality and reliability.
- Troubleshoot complex data engineering and integration issues with a focus on scalability, performance, and maintainability.
- Apply sound software engineering practices across coding, testing, CI/CD, version control,



deployment, and documentation.
- Stay up to date with technology trends and best practices relevant to modern data platforms and integration engineering.

Collaboration and team contribution

- - Partner with cross-functional stakeholders to design and deliver data and integration solutions that meet business needs.
- Collaborate with peers in FinOps, Data Architecture, Data Governance, Cloud Engineering, and Observability to support end-to-end delivery.
- Play a leadership role in project execution and in solving complex technical problems.
- Help train and mentor junior engineers.
- Communicate clearly on technical approach, delivery progress, dependencies, and risks.

Technologies we use

- - Visual Studio, JIRA, Confluence, Git
- Python for core development
- SQL and dbt for data modeling and transformation
- FiveTran and dltHub for data ingestion
- Databricks and Google Cloud Platform for the modern data platform
- Power BI for reporting and analytics enablement
- MuleSoft and Informatica for integration engineering
- PostgreSQL, SQL Server, Snowflake, and BigQuery as data stores and legacy/current platforms
- Apache Airflow, Power BI Dataflows, and GitHub Actions for orchestration and automation
- Datadog for observability
- Terraform and Ansible for infrastructure and configuration automation
- Microsoft Azure and GCP in parts of the broader ecosystem

What we are looking for

- 5+ years of experience in data engineering, analytics engineering, integration engineering, migration engineering, software engineering, or related fields.
- Demonstrated expertise in both traditional and modern data systems, with hands-on experience building scalable and reliable solutions.
- Strong hands-on experience with modern data platform technologies such as Databricks, dbt, GCP, Snowflake, PostgreSQL, BigQuery, Power BI, and related tools.
- Hands-on experience building integrations in MuleSoft and supporting, enhancing, or modernizing legacy integrations in Informatica.
- Proficiency in software engineering principles, including CI/CD pipelines, version control, RESTful APIs, Python, and SQL.
- Familiarity with orchestration and automation tooling such as Airflow, GitHub Actions, and related platforms.
- Familiarity with observability tooling such as Datadog.
- Experience with validation, reconciliation, monitoring, and production support for data pipelines and integration services.
- Strong problem-solving abilities and an execution-oriented mindset.
- Robust communication and collaboration skills.
- Google Cloud Professional Data Engineer certification is a plus.
- Familiarity with Terraform and/or Ansible is a plus.
- Experience working for a SaaS company is a plus.

#Intermediate

Pay Range

INR 2,250,000.00 - INR 3,600,000.00 /Yr.

Location

Chennai, India

About the role & team

We are seeking a Senior Data Engineer to help scale Kinaxis’ Migrations and Data Integrations capabilities. This is a hands-on engineering role focused on building, migrating, maintaining, and supporting data assets and integrations that enable Kinaxis’ modernization journey.

You will help migrate pipelines, transformations, data models, orchestration workflows, observability/reporting dependencies, and related components from legacy platforms such as Snowflake, PostgreSQL, SQL Server, Airflow, Grafana, Informatica, and related tools into the modern Kinaxis stack built on Databricks, GCP, dbt, Power BI, and cloud-native orchestration and observability tooling.

You will also build new application-to-application connectors in MuleSoft, while maintaining, troubleshooting, enhancing, and selectively migrating existing integrations currently implemented in Informatica.

This role is ideal for an engineer who enjoys practical modernization work: rebuilding legacy assets in modern technologies, improving reliability and supportability, and creating reusable patterns that accelerate platform transition at scale.

Key responsibilities

Migrations and delivery

- - Build and migrate data pipelines, transformations, and models into the modern data platform using Databricks, GCP,



dbt, Power BI, and related tooling.
- Refactor, rebuild, or migrate legacy data assets currently implemented in platforms such as Snowflake, PostgreSQL, SQL Server, Airflow, Grafana, Informatica, and similar systems.
- Develop reusable migration components, templates, validation checks, and automation assets that improve speed, consistency, and quality across modernization initiatives.
- Support validation, reconciliation, issue triage, testing, and cutover-readiness activities for migrated assets.
- Contribute to runbooks, technical documentation, and delivery standards that make the Migration Factory repeatable and scalable.

Data Integrations engineering

- - Build and maintain new application-to-application connectors in MuleSoft.
- Maintain, troubleshoot, and enhance existing integrations built in Informatica any Python, ensuring reliability and operational supportability.
- Migrate or refactor selected legacy Informatica integrations into modern integration patterns and platforms where appropriate.
- Implement integration logic using APIs, file-based interfaces, orchestration workflows, and batch or event-driven processing patterns.
- Develop validation, monitoring, reconciliation, and error-handling mechanisms to ensure production-ready integrations.

Engineering and operational excellence

- - Build and maintain robust, scalable, and efficient data pipelines for batch and streaming use cases.
- Implement data validation, cleansing, and error-handling mechanisms to maintain high data quality and reliability.
- Troubleshoot complex data engineering and integration issues with a focus on scalability, performance, and maintainability.
- Apply sound software engineering practices across coding, testing, CI/CD, version control, deployment, and documentation.
- Stay up to date with technology trends and best practices relevant to modern data platforms and integration engineering.

Collaboration and team contribution

- - Partner with cross-functional stakeholders to design and deliver data and integration solutions that meet business needs.
- Collaborate with peers in FinOps, Data Architecture, Data Governance, Cloud Engineering, and Observability to support end-to-end delivery.
- Play a leadership role in project execution and in solving complex technical problems.
- Help train and mentor junior engineers.
- Communicate clearly on technical approach, delivery progress, dependencies, and risks.

Technologies we use

- - Visual Studio, JIRA, Confluence, Git
- Python for core development
- SQL and dbt for data modeling and transformation
- FiveTran and dltHub for data ingestion
- Databricks and Google Cloud Platform for the modern data platform
- Power BI for reporting and analytics enablement
- MuleSoft and Informatica for integration engineering
- PostgreSQL, SQL Server, Snowflake, and BigQuery as data stores and legacy/current platforms
- Apache Airflow, Power BI Dataflows, and GitHub Actions for orchestration and automation
- Datadog for observability
- Terraform and Ansible for infrastructure and configuration automation
- Microsoft Azure and GCP in parts of the broader ecosystem

What we are looking for

- 5+ years of experience in data engineering, analytics engineering, integration engineering, migration engineering, software engineering, or related fields.
- Demonstrated expertise in both traditional and modern data systems, with hands-on experience building scalable and reliable solutions.
- Strong hands-on experience with modern data platform technologies such as Databricks, dbt, GCP, Snowflake, PostgreSQL, BigQuery, Power BI, and related tools.
- Hands-on experience building integrations in MuleSoft and supporting, enhancing, or modernizing legacy integrations in Informatica.
- Proficiency in software engineering principles, including CI/CD pipelines, version control, RESTful APIs, Python, and SQL.
- Familiarity with orchestration and automation tooling such as Airflow, GitHub Actions, and related platforms.
- Familiarity with observability tooling such as Datadog.
- Experience with validation, reconciliation, monitoring, and production support for data pipelines and integration services.
- Strong problem-solving abilities and an execution-oriented mindset.
- Strong communication and collaboration skills.
- Google Cloud Professional Data Engineer certification is a plus.
- Familiarity with Terraform and/or Ansible is a plus.
- Experience working for a SaaS company is a plus.

#Intermediate

📌 Senior Engineer, Data & Analytics - IND (Chennai)
🏢 Midwest Express Clinic
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