Senior Data Integration Engineer

Job Title:Senior Data Integration Engineer

Notice Period: Immediate to 30 days

Experience Required: 5+ Years

Job Location: Pune/Hybrid

About Accelirate

Accelirate is a leading agentic AI and automation firm, building intelligent agents that transform enterprise operations. We're a certified partner of UiPath, Microsoft, and Salesforce, with 1500+ processes automated annually across industries. Honored as a Top Workplaces USA winner five years in a row, we're known for delivering scalable, agent-driven solutions that empower humans, agents, and robots to work smarter together.

About the Role We are seeking a Senior Data Integration Engineer to join our growing platform team. In this role, you will lead the design and implementation of scalable, real-time data integration pipelines to connect and harmonize diverse Enterprise Resource Planning (ERP) systems across our organization. You will leverage event-driven architectures to ensure seamless, high-throughput, and low-latency data movement between enterprise platforms.

Key Responsibilities

• Pipeline Architecture & Development: Design, build, and deploy robust, real-time, and batch data pipelines integrating disparate ERP with downstream data lakes and platforms.
• Event-Driven Systems: Leverage Apache Kafka, Kafka Connect, and stream processing engines (Kafka Streams or Apache Flink) to process and transform high-volume change data capture (CDC) and transactional data.
• Service & API Engineering: Build resilient microservices and integration layers using Java and Spring Boot to orchestrate complex data flows and enterprise APIs.
• Containerization & Orchestration: Package applications into Docker containers and manage scalable deployments, service discovery, and container orchestration via Kubernetes.
• Data Modeling & Storage: Optimize multi-database environments across relational systems including PostgreSQL, MySQL, SQL Server, and Oracle.
• DevOps & Automation: Manage Infrastructure as Code (IaC) using Terraform or AWS CloudFormation, and build automated CI/CD deployment pipelines using GitHub Actions.
• Observability & Reliability: Set up end-to-end monitoring, APM, log management, and alerting using tools like DataDog, New Relic, or Splunk to ensure data pipeline health and transactional accuracy.

Required Qualifications

• Core Engineering: 5+ years of software/data engineering experience with strong proficiency in Java (Spring Boot) and Python.
• Streaming & Messaging: Hands-on experience building event-driven systems using Apache Kafka, Kafka Connect (source/sink connectors, CDC), and Kafka Streams or Apache Flink.
• Containerization: Hands-on experience containerizing applications with Docker and managing workloads on Kubernetes.
• Monitoring & Observability: Production experience setting up metrics, tracing, and logging dashboards using platforms like DataDog, New Relic, or Splunk.
• Database Expertise: Deep expertise in relational database design, query optimization, and schema management across engines such as PostgreSQL, MySQL, SQL Server, or Oracle.
• Cloud Infrastructure: Hands-on experience deploying scalable applications and data workloads on AWS.
• Infrastructure as Code (IaC) & CI/CD: Demonstrated experience writing Terraform or AWS CloudFormation scripts and managing CI/CD workflows via GitHub Actions.
• Version Control: Advanced proficiency with Git and standard collaborative workflows.

Preferred Qualifications

• Prior experience working directly with enterprise ERP data models.
• Experience implementing Change Data Capture (CDC) tools (e.g., Debezium) inside Kubernetes clusters.
• Familiarity with enterprise data warehousing concepts and stream-table joins.