Key Responsibilities:Design, build, and maintain CI/CD pipelines using Azure DevOps for automated testing, container image builds, and deploymentContainerise the data quality platform using Docker and manage deployment of container images across Business environments using KubernetesSpin up and configure new container instances when onboarding new Business areas onto the platformDevelop and maintain automated testing frameworks covering unit, integration, and end-to-end testingDesign, build, and expose RESTful APIs to integrate the platform with upstream and downstream systemsCollaborate with the Data Architecture team to ensure platform components are modular, platform-agnostic, and deployable across cloud and on-premise environmentsWork with Azure services including Azure Container Registry, Azure Kubernetes Service, Azure Key Vault, Azure Blob Storage, and Azure DevOpsDevelop and optimise data pipelines using PySpark and SQL ServerSupport the integration of Databricks workloads into the platform architectureEnsure platform security standards are met including secret management, image vulnerability scanning, and access controlsContribute to technical documentation, runbooks, and onboarding guides for Business teamsRequired Skills & Experience:8–12 years of experience in data engineering or platform engineering rolesStrong hands-on experience with Azure services — AKS, ACR, Key Vault, Blob Storage,



Azure DevOpsProven experience containerising applications using Docker and orchestrating with KubernetesSolid experience building and maintaining CI/CD pipelines in Azure DevOpsExperience designing and building RESTful APIsProficiency in PySpark and SQL ServerExperience with Databricks — job orchestration, cluster management, notebook developmentStrong understanding of software testing practices — unit testing, integration testing, end-to-end testingExperience with branching strategies, versioning, and release managementStrong problem-solving skills and ability to work independently in a fast-paced environmentPreferred Skills:Understanding of Data Quality concepts — profiling, validation rules, DQ scoring, observabilityExperience with data quality tooling such as Informatica, Outstanding Expectations, or similarFamiliarity with Flask or similar Python web frameworksExperience with modular, microservice-style architecture designWhat We're Looking For:Beyond 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.

📌 Senior Data Engineer (Bengaluru)
🏢 TEKsystems
📍 Bengaluru