Teams at Nexaminds

Build and maintain scalable data pipelines, ETL/ELT processes, data models, metric definitions, and data infrastructure. Develop production solutions with Python, SQL, Spark, dbt, Fivetran, Airflow, Databricks, Azure, and cloud storage. Collaborate with data scientists, engineers, analysts, and stakeholders to deliver reliable, accessible data and self-service tools. Troubleshoot pipeline issues, improve data quality and scalability, and use AI-assisted development tools to accelerate engineering work.

Lead an internal developer platform and productivity engineering team in a player-coach role. Manage distributed teams, sprint delivery, performance, hiring, and stakeholder communication while contributing to architecture, technical decisions, coding, and platform delivery. Drive cloud infrastructure, CI/CD, developer tooling, agile execution, and adoption of AI-assisted development tools. Partner with product, DevOps, and QA teams to manage capacity, dependencies, risks, and roadmap execution.

Design, build, operate, and scale change data capture pipelines using Debezium, Kafka or Azure Event Hubs, and Databricks. Manage streaming data across hundreds of databases and thousands of tables, ensuring reliability, low latency, schema consistency, and data quality. Troubleshoot replication lag, schema drift, backpressure, and recovery issues. Collaborate with backend and data teams on schemas and SLAs while documenting architecture and operational procedures.