Job DescriptionKey Responsibilities

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- Design, build, and maintain CI/CD pipelines using Azure DevOps for automated testing, container image builds, and deployment
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- Containerise the data quality platform using Docker and manage deployment of container images across Business environments using Kubernetes
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- Spin up and configure new container instances when onboarding recent Business areas onto the platform
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- Develop and maintain automated testing frameworks covering unit, integration, and end-to-end testing
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- Design, build, and expose RESTful APIs to integrate the platform with upstream and downstream systems
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- Collaborate with the Data Architecture team to ensure platform components are modular, platform-agnostic, and deployable across cloud and on-premise environments
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- Work with Azure services including Azure Container Registry, Azure Kubernetes Service, Azure Key Vault, Azure Blob Storage, and Azure DevOps
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- Develop and optimise data pipelines using PySpark and SQL Server
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- Support the integrationof Databricks workloads into the platform architecture
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- Ensure platform security standards are met including secret management, image vulnerability scanning, and access controls
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- Contribute to technicaldocumentation, runbooks, and onboarding guides for Business teams
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nRequired Skills & Experience:

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- 8–12 years of experience in data engineering or platform engineering roles
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- Strong hands-on experience with Azure services — AKS, ACR, Key Vault,



Blob Storage, Azure DevOps
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- Proven experience containerising applications using Docker and orchestrating with Kubernetes
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- Solid experience building and maintaining CI/CD pipelines in Azure DevOps
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- Experience designing and building RESTful APIs
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- Proficiency in PySpark and SQL Server
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- Experience with Databricks — job orchestration, cluster management, notebook development
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- Strong understanding ofsoftware testing practices — unit testing, integration testing, end-to-end testing
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- Experience with branching strategies, versioning, and release management
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- Strong problem-solving skills and ability to work independently in a fast-paced environment
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nPreferred Skills:

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- Understanding of Data Quality concepts — profiling, validation rules, DQ scoring, observability
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- Experience with data quality tooling such as Informatica, Great Expectations, or similar
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- Familiarity with Flask or similar Python web frameworks
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- Experience with modular, microservice-style architecture design
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nWhat We're LookingFor:

NBeyond technical skills, we are looking for someone who takes ownership, thinks like a platform engineer, and understands that the best infrastructure is the kind that Business teams never have to think about. The ideal candidate is equally comfortable writing a Dockerfile, debugging a failing pipeline, and discussing deployment governance with a non-technical stakeholder.

📌 Hiring: Senior Data Engineer (Karnataka)
🏢 TEKsystems
📍 Karnataka