Snaplogic Engineer

Valuelabs; India; Remote; INR 11,429,000 - 14,286,000; Full time

Job summary

Valuelabs is seeking a Data Engineering Specialist focused on streaming and integration to design robust pipelines for real-time analytics. You will build and optimize data flows using SnapLogic and Confluent Kafka across cloud, SaaS, and on-prem systems.

The role requires collaboration with data scientists and application teams, implementing security, governance, and observability with Grafana and Prometheus, and contributing to CI/CD and documentation in a remote-first environment.

Qualifications

• Bachelor’s or Master’s in CS, Eng, or related field.
• 4+ years in data engineering with streaming focus.
• Experience with Confluent Kafka (producers/consumers, topics, partitioning).
• Hands-on SnapLogic: integration cloud development and deployment.
• Cloud platforms (AWS/Azure/GCP) and containers (Docker/Kubernetes).
• Python or Bash scripting; IaC familiarity (Terraform/CloudFormation).
• Knowledge of data security, governance, and compliance (GDPR, SOC 2).

Responsibilities

• Design, develop, and maintain high-throughput, low-latency data pipelines using SnapLogic and Confluent Kafka.
• Architect and implement event-driven systems using Kafka for real-time data ingestion, processing, and distribution across microservices and downstream analytics platforms.
• Configure and manage SnapLogic integration workflows for secure, reliable, and automated data movement between SaaS, on-premise, and cloud applications.
• Collaborate with data scientists, analysts, and application teams to understand data needs and deliver scalable integration solutions.
• Optimize Kafka cluster performance, monitor stream health, and ensure data durability, consistency, and fault tolerance.
• Implement data quality checks, schema evolution strategies, and observability using tools like Confluent Control Center, Grafana, and Prometheus.
• Ensure security and compliance in data flows through encryption, access control, and audit logging.
• Participate in agile ceremonies and contribute to technical documentation, release planning, and CI/CD practices.
• Stay current with evolving trends in streaming data, integration platforms, and cloud-native data architectures.

Skills

Streaming data

Data engineering

Kafka

SnapLogic

Cloud platforms

Python scripting

Education

Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field

Tools

SnapLogic Integration Cloud

Confluent Kafka

Docker

Kubernetes

Terraform

Grafana

Prometheus

Confluent Control Center

Job description

Job Title: Data Engineering Specialist (Streaming & Integration)

Department: Data & Analytics

Reports To: Data Engineering Manager

Location: Remote (Global)

Employment Type: Full-Time

Overview

We are seeking a highly skilled Data Engineering Specialist with deep expertise in real-time data streaming and integration platforms to join our growing data team. The ideal candidate will have hands-on experience with SnapLogic and Confluent Kafka, and will be responsible for designing, building, and maintaining robust, scalable data pipelines that enable real-time analytics, operational intelligence, and seamless integration across enterprise systems.

Key Responsibilities

• Design, develop, and maintain high-throughput, low-latency data pipelines using SnapLogic and Confluent Kafka.
• Architect and implement event-driven systems using Kafka for real-time data ingestion, processing, and distribution across microservices and downstream analytics platforms.
• Configure and manage SnapLogic integration workflows for secure, reliable, and automated data movement between SaaS, on-premise, and cloud applications.
• Collaborate with data scientists, analysts, and application teams to understand data needs and deliver scalable integration solutions.
• Optimize Kafka cluster performance, monitor stream health, and ensure data durability, consistency, and fault tolerance.
• Implement data quality checks, schema evolution strategies, and observability using tools like Confluent Control Center, Grafana, and Prometheus.
• Ensure security and compliance in data flows through encryption, access control, and audit logging.
• Participate in agile ceremonies and contribute to technical documentation, release planning, and CI/CD practices.
• Stay current with evolving trends in streaming data, integration platforms, and cloud-native data architectures.

Required Qualifications

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
• 4+ years of professional experience in data engineering with a focus on streaming data and integration.
• Proven experience with Confluent Kafka: building producers/consumers, managing topics, handling partitioning, replication, and stream processing using Kafka Streams or KSQL.
• Extensive hands-on experience with SnapLogic, including building, testing, and deploying integrations using the SnapLogic Integration Cloud.
• Strong understanding of data modeling, ETL/ELT processes, and data pipeline orchestration.
• Experience with cloud platforms (AWS, Azure, or GCP) and containerized environments (Docker, Kubernetes).
• Proficiency in scripting languages (Python, Bash) and familiarity with infrastructure as code (Terraform, CloudFormation).
• Knowledge of data security, governance, and compliance standards (e.g., GDPR, SOC 2).
• Excellent communication skills and ability to work in a collaborative, remote-first environment.