Track Lead - Saviynt, Java

Technology, Data & Digital · Data, AI & Analytics · Data Engineering

In short

Seeking a skilled Real-Time, Low-Latency Data Engineer with 5+ years of experience to design and optimize high-performance data platforms processing large-scale streaming data. The role involves developing streaming solutions using technologies like Kafka, Flink, and Spark Streaming, implementing event-driven architectures, and collaborating with stakeholders to deliver robust data solutions.

Responsibilities

Design, build, and maintain scalable real-time data pipelines with low latency and high throughput.
Develop and optimize streaming data solutions using technologies such as Apache Kafka, Apache Flink, Spark Streaming, Dataflow, or equivalent platforms.
Implement event-driven architectures and data ingestion frameworks for near real-time analytics and operational use cases.
Collaborate with data scientists, application teams, product owners, and business stakeholders to understand data requirements and deliver robust solutions.
Optimize data processing performance, reliability, fault tolerance, and system observability.
Design and implement data models, schemas, and storage solutions for real-time and historical data consumption.
Build monitoring, alerting, and automated recovery mechanisms to ensure platform availability and service reliability.
Ensure data quality, governance, security, and compliance standards are embedded within data engineering processes.
Participate in architecture reviews, code reviews, and DevOps practices including CI/CD and infrastructure automation.
Troubleshoot complex production issues and perform root cause analysis for streaming and distributed systems.

Requirements

Bachelor's or Master's degree in Computer Science, Engineering, Information Systems, or related discipline.
5+ years of experience in data engineering, with significant exposure to real-time streaming data platforms.
Strong programming skills in Python, Java, or Scala.
Hands-on experience with Kafka, Flink, Spark Streaming, Kafka Streams, or similar stream processing frameworks.
Expertise in SQL and NoSQL databases such as PostgreSQL, Cassandra, MongoDB, DynamoDB, or Redis.
Strong understanding of distributed systems, message queues, event sourcing, and microservices architectures.
Experience with cloud platforms such as Azure, AWS, or Google Cloud Platform.
Proficiency in containerization and orchestration technologies such as Docker and Kubernetes.
Experience with CI/CD pipelines, Infrastructure as Code (Terraform, ARM Templates, CloudFormation), and DevOps methodologies.
Strong problem-solving, analytical, and communication skills.

Desired Qualifications

Experience with low-latency trading, IoT, telemetry, fraud detection, or real-time customer analytics platforms.
Knowledge of lakehouse architectures, Delta Lake, Iceberg, or Hudi.
Exposure to ML feature stores and real-time AI/ML inference pipelines.
Industry certifications in cloud, data engineering, or streaming technologies.

Benefits

Flexible/Hybrid work location.
Work with cutting-edge cloud and data technologies.
Opportunity to power next-generation analytics and digital experiences.
Contribute to critical business outcomes through data solutions.

Skills

JavaSaviyntPythonScalaKafkaFlinkSpark StreamingDataflowSQLNoSQLPostgreSQLCassandraMongoDBDynamoDBRedisAWSAzureGoogle Cloud PlatformDockerKubernetesCI/CDTerraformARM TemplatesCloudFormationDevOps

#Data Engineer#Real-Time Data#Low-Latency#Streaming Data#Data Pipelines#Apache Kafka#Apache Flink#Spark Streaming#Event-Driven Architecture#Cloud#Big Data#Data Engineering#Distributed Systems#Microservices

About HCLTech

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HCLTech is a global technology company, home to 219,000+ people across 54 countries, delivering industry-leading capabilities centered around digital, engineering and cloud, powered by a broad portfolio of technology services and products. We work with clients across all major verticals, providing industry solutions for Financial Services, Manufacturing, Life Sciences and Healthcare, Technology and Services, Telecom and Media, Retail and CPG, and Public Services. Consolidated revenues as of 12 months ending September 2022 totaled $12.1 billion. To learn how we can supercharge progress for…

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