1. Principal Data Architect / Principal Data Engineer

Experience: 15–20 years

Role Overview ( US Based Company )

We are looking for a Principal Data Architect / Principal Data Engineer with deep expertise in large-scale data platforms, real-time streaming architectures, Change Data Capture, and enterprise data warehouse solutions.

This role will be responsible for designing and evolving the data architecture behind our SaaS platform, including real-time and batch data ingestion, large-scale transformation pipelines, distributed data processing, data warehousing, and data movement between customer environments and our cloud platform.

The ideal candidate should have extensive hands-on experience with Debezium, Kafka or similar distributed streaming platforms, CDC-based architectures, enterprise data warehousing, and high-volume transactional systems.

This is not purely an architecture or advisory role. We expect the individual to remain technically hands-on and capable of designing, reviewing, troubleshooting, and improving complex production systems.

Key Responsibilities

- Design and own enterprise-scale data architectures supporting both real-time and batch workloads.
- Architect scalable Change Data Capture solutions using Debezium and related technologies.
- Design event-driven and streaming architectures using Kafka, Event Hubs, Pulsar, or equivalent platforms.
- Define patterns for reliable data ingestion from customer databases and external systems.
- Design fault-tolerant pipelines capable of processing high-volume transactional data.
- Build and optimize enterprise data warehouse and analytical data platform architectures.
- Design data models supporting operational reporting, analytics,



machine learning, and AI workloads.
- Establish architectural patterns for data partitioning, replication, retention, replay, and schema evolution.
- Design strategies for handling late-arriving data, duplicates, backpressure, failed events, and data reconciliation.
- Improve scalability and reliability of existing ETL/ELT and streaming pipelines.
- Work closely with application, database, cloud, DevOps, analytics, and AI engineering teams.
- Review existing architectures and identify performance, scalability, and reliability bottlenecks.
- Support customer onboarding involving large-volume database migrations and data integration.
- Establish engineering standards for observability, data quality, lineage, monitoring, and recoverability.
- Mentor senior engineers and provide architectural guidance across engineering teams.
- Participate in production incident analysis and complex performance troubleshooting.
- Evaluate new data technologies and determine where they provide meaningful engineering value.

Required Technical Expertise

- 15–20 years of experience in data engineering, distributed systems, or data architecture.
- Deep expertise with Debezium and Change Data Capture architectures.
- Strong experience with Apache Kafka or equivalent distributed event-streaming technologies.




- Solid understanding of Kafka topics, partitions, consumer groups, offsets, retention, rebalancing, replication, ordering, and delivery semantics.
- Experience building high-throughput, low-latency streaming platforms.
- Strong understanding of event-driven and asynchronous architectures.
- Extensive experience with enterprise data warehouse platforms.
- Strong knowledge of dimensional modeling, data marts, star schemas, normalized and denormalized models.
- Strong SQL and database engineering skills.
- Experience working with large transactional databases and datasets containing hundreds of millions or billions of records.
- Strong knowledge of Azure, AWS, or GCP data services.
- Experience with technologies such as Azure Data Factory, Databricks, Spark, Snowflake, Synapse, Fabric, or equivalent.
- Strong understanding of distributed system concepts including consistency, fault tolerance, idempotency, retries, checkpointing, and recovery.
- Experience designing both streaming and batch processing systems.
- Strong understanding of data security, governance, privacy, and tenant isolation.

Preferred Experience

- Azure Event Hubs.
- Azure SQL and SQL Server.
- Apache Flink
- Databricks / Apache Spark.
- Large multi-tenant SaaS platforms.
- Near-real-time analytical platforms.
- Data migration and customer onboarding.
- Data platform modernization initiatives.
- AI/ML data platform architecture.

Pay: ₹2,000,000.00 - ₹6,000,000.00 per year

Benefits

- Commuter assistance
- Flexible schedule
- Health insurance
- Life insurance
- Paid sick time
- Provident Fund

Work Location: Hybrid remote in Chennai, Tamil Nadu 600011

📌 Principal Data Architect / Principal Data Engineer (Chennai)
🏢 Multisolution Business Services
📍 Chennai