Senior Data Engineer(6+ years with MS Fabric, Azure, ADF, Data Platforms only)
Wolters Kluwer10 days ago
Chennai, IndiaSenior
Responsibilities
- Design, develop, and maintain scalable data pipelines for operational, analytical, reporting, and AI use cases.
- Build ingestion, transformation, orchestration, delivery, data modeling, and reusable data engineering components.
- Design enterprise integrations and secure REST and GraphQL APIs across applications, platforms, and third-party systems.
- Implement event-driven, asynchronous, messaging, authentication, authorization, versioning, monitoring, and API lifecycle patterns.
- Build automated data validation, reconciliation, testing, monitoring, observability, and quality controls.
- Troubleshoot production issues, investigate incidents, perform root-cause analysis, and improve reliability, resiliency, performance, and cost.
- Use AI-assisted development for design, coding, testing, documentation, troubleshooting, and optimization with appropriate technical validation.
- Develop governed and auditable solutions incorporating data quality, lineage, metadata, security, compliance, and sensitive-data requirements.
- Own solutions through development, deployment, and production operation, including deployment, testing, configuration, and operational automation.
- Collaborate on architecture and technical design, communicate technical tradeoffs, share reusable solutions, and mentor less-experienced engineers when appropriate.
Requirements
- Bachelor’s degree in Computer Science, Engineering, Information Systems, or a related discipline, or equivalent practical experience.
- 6+ years of experience in data engineering, integration engineering, software engineering, or related roles.
- Strong SQL skills, including data modeling, database design, and performance optimization.
- Hands-on experience designing and developing scalable ETL/ELT pipelines and data-processing solutions.
- Experience with one or more modern cloud data platforms such as Databricks, Microsoft Fabric, Snowflake, or comparable technologies.
- Programming experience with Python, PySpark, Scala, Java, C#, or a comparable language.
- Experience developing and consuming REST APIs and working with API-based architectures.
- Experience with event-driven, messaging, or asynchronous integration patterns.
- Experience with cloud-native technologies across Azure, AWS, GCP, or comparable environments.
- Experience with source control, automated testing, CI/CD, monitoring, and modern DevOps practices.
- Understanding of data quality, governance, security, lineage, and cloud identity concepts.
- Experience supporting production data systems and troubleshooting complex technical issues.
- Practical experience using AI-assisted development tools in day-to-day engineering.
- Strong problem-solving, communication, and collaboration skills.
- Preferred experience includes multiple modern data platforms or cloud technologies, Apache Spark, Delta Lake, Apache Iceberg, lakehouse architectures, GraphQL, API management, Kafka, Event Hubs, Event Grid, Service Bus, serverless computing, data products, Infrastructure as Code, deployment automation, RAG, semantic models, data agents, machine learning, agent/tool integrations, and highly governed or regulated data.
Tech Stack
Categories
Data Engineering
About Wolters Kluwer
Wolters Kluwer builds subscription software, data, and workflow solutions for professionals in healthcare, tax and accounting, legal and regulatory, finance and compliance, and ESG. Its portfolio spans SaaS applications and expert content that support compliance, decision-making, and operational processes. Founded in 1836 and headquartered in Alphen aan den Rijn, the Netherlands, it is publicly traded on Euronext Amsterdam (WKL) and reported 2025 annual revenue of €6.1 billion.