Track Lead - Saviynt, Java

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

In short

We are seeking a skilled Real-Time, Low-Latency Data Engineer with over 5 years of experience to design and optimize high-performance data platforms processing large-scale streaming data. The role involves developing real-time data pipelines, implementing event-driven architectures, and collaborating with various teams to deliver robust data solutions on cloud platforms.

Responsibilities

Design, build, and maintain scalable real-time data pipelines.
Develop and optimize streaming data solutions using technologies like Kafka, Flink, Spark Streaming, or Dataflow.
Implement event-driven architectures and data ingestion frameworks.
Collaborate with data scientists, application teams, product owners, and business stakeholders.
Optimize data processing performance, reliability, fault tolerance, and system observability.
Design and implement data models, schemas, and storage solutions.
Build monitoring, alerting, and automated recovery mechanisms.
Ensure data quality, governance, security, and compliance standards.
Participate in architecture reviews, code reviews, and DevOps practices.
Troubleshoot complex production issues and perform root cause analysis.

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 (PostgreSQL, Cassandra, MongoDB, DynamoDB, Redis).
Strong understanding of distributed systems, message queues, event sourcing, and microservices architectures.
Experience with cloud platforms (Azure, AWS, or Google Cloud Platform).
Proficiency in containerization and orchestration technologies (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.
Opportunity to work with cutting-edge cloud and data technologies.
Be part of a team driving real-time analytics and business-critical decision-making.

Skills

JavaPythonScalaKafkaFlinkSpark StreamingDataflowSQLPostgreSQLCassandraMongoDBDynamoDBRedisAWSAzureGoogle Cloud PlatformDockerKubernetesCI/CDTerraformARM TemplatesCloudFormationSaviynt

#Real-Time#Low-Latency#Data Engineer#Streaming Data#Data Pipelines#Event-Driven Architecture#Cloud#Analytics#Distributed Systems#Python#Java#Scala#Kafka#Flink#Spark Streaming#SQL#NoSQL#AWS#Azure#GCP#Docker#Kubernetes#CI/CD#DevOps#Saviynt

About HCLTech

Supercharging progress through technology and innovation

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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