Senior data engineer – spark streaming & kafka
Kagool · India
Job Description
About Kagool
We are a fast-growing IT consultancy specializing in the transformation of complex Global enterprises that use SAP. We are looking for hard working individuals to help deliver for our global customer base. We embrace the opportunities of the future and work proactively to make good use of technology. As you can imagine, this means that we have a vibrant and diverse mix of skills and people making Kagool a great place to work.
Job Summary
We are looking for an experienced Senior Data Engineer with 7+ years of experience in designing, developing, and supporting scalable data engineering solutions.
The ideal candidate must have strong hands-on experience with Apache Spark, Py Spark, Kafka, Spark Structured Streaming, Python, SQL, and Microsoft Azure. The candidate should have practical experience implementing and managing Kafka-based streaming solutions on Azure and working with real-time data processing pipelines.
Azure experience is mandatory for this role.
Key Responsibilities
Design, develop, and maintain scalable batch and real-time data pipelines using Apache Spark and Py Spark. Develop and support Kafka-based real-time streaming pipelines on Microsoft Azure. Implement real-time data processing using Spark Structured Streaming. Work with Kafka topics, partitions, consumer groups, offsets, retention, and message delivery mechanisms. Implement Kafka producers and consumers for high-volume data ingestion and processing. Integrate Apache Kafka with Azure data services and downstream data platforms. Develop data transformation, cleansing, aggregation, and enrichment processes. Implement checkpointing, fault tolerance, error handling, retry mechanisms, and recovery strategies for streaming applications. Design and optimize Spark jobs for performance, scalability, and efficient resource utilization. Work with Azure data services such as Azure Databricks, ADLS Gen2, Azure Event Hubs, Azure Data Factory, and Azure Synapse Analytics. Develop SQL queries and work with relational and analytical databases. Implement data quality and validation frameworks. Troubleshoot production issues and perform root-cause analysis. Collaborate with Data Architects, Application Teams, Dev Ops, and Business stakeholders. Participate in technical design discussions, code reviews, and CI/CD activities.Mandatory Technical Skills
7+ years of experience in Data Engineering / Big Data. Strong hands-on experience with Apache Spark and Py Spark. Strong hands-on experience with Apache Kafka. Mandatory hands-on experience with Kafka on Azure. Mandatory Microsoft Azure experience. Strong experience with Spark Structured Streaming. Strong programming skills in Python. Strong SQL skills. Experience designing and developing real-time/streaming data pipelines. Good understanding of distributed computing and Big Data architecture.Hands-on experience with Kafka:
Topics and partitions Producers and consumers Consumer groups Offsets Retention Partitioning Error handling and recoveryStrong understanding of Spark concepts including:
Partitioning Shuffling Joins Caching Serialization Performance tuningHands-on experience with Azure Databricks and/or Azure data engineering services.
Experience with Git and CI/CD practices.
Azure Skills
Candidates must have practical experience with one or more of the following:
Azure Databricks
Azure Event Hubs
Azure Data Factory
Azure Data Lake Storage Gen2
Azure Synapse Analytics
Azure Functions
Azure Monitor
Azure Key Vault
Microsoft Entra ID / Azure authentication
Azure Kafka Requirement
The candidate should have hands-on implementation/support experience with Kafka in an Azure environment, including experience with:
Kafka deployment/integration on Azure
Kafka producers and consumers
Kafka topics and partitions
Consumer groups and offset management
Kafka-to-Spark streaming integration
Monitoring and troubleshooting Kafka workloads
Performance tuning and scalability
Security/authentication for Kafka workloads on Azure
Good to Have
Delta Lake Delta Live Tables Kafka Connect Confluent Kafka / Confluent Cloud Schema Registry Avro Azure Event Hubs Kubernetes Terraform Azure Dev Ops Prometheus / Grafana CI/CD automationCandidate Profile
The candidate should be comfortable working on large-scale; high-throughput streaming systems and should have experience taking data pipelines from design and development through production deployment and operational support.
Career at Kagool
A career at Kagool will give you a path towards progression and opportunities, with the current rate of growth we at Kagool have dedicated time towards individual growth, recognizing individual contributions, filling the team with a strong sense of purpose along with providing a fun, flexible and friendly work environment
Details
| Company | Kagool |
| Location | India |
| Type | FULL TIME |
| Niche | tech |
| Experience | permanent |