Overview

As a Backend Developer and DevOps Engineer at InterIntel Technologies Limited, I built scalable data-processing workflows, automated infrastructure operations, and supported cloud-based communication systems. My work combined Python backend development, data engineering, deployment automation, observability, and production support.

Key Responsibilities and Achievements

  • Planned and implemented scalable data pipelines with Apache Spark, Cassandra, and PostgreSQL to process large data volumes for analytics and real-time decision-making.
  • Designed ETL functions, packages, and pipelines to extract, transform, and load data from databases, APIs, spreadsheets, and flat files.
  • Identified and resolved SQL query and ETL bottlenecks, improving data retrieval and loading performance.
  • Automated streaming ETL workflows with Faust to process and transform high-volume analytics data.
  • Deployed and managed a GitOps delivery pipeline with ArgoCD and Helm for microservices across staging and production Kubernetes clusters.
  • Monitored infrastructure with Prometheus and Grafana, creating alerts for resource bottlenecks and service failures.
  • Developed Bash and Python scripts to automate server configuration, backups, and log rotation.
  • Delivered a cloud-based customer service solution using AudioCodes Virtual Edition SBC and Microsoft Teams Direct Routing.

Data Pipeline Development and Integration

I created reusable ETL components and end-to-end workflows that improved data quality, processing efficiency, and maintainability across multiple sources and targets.

Example ETL pipeline

Pipeline Design and Performance

  • Configured connectors for PostgreSQL, spreadsheets, CSV files, APIs, and other data sources.
  • Implemented data-quality and integrity checks to keep transformed data accurate and consistent.
  • Built transformation functions with pandas and Apache Spark for cleaning, standardization, aggregation, and format conversion.
  • Optimized loading through bulk inserts, batching, prepared statements, asynchronous operations, partitioning, and incremental loads.
  • Restructured complex SQL queries and optimized joins and partitioning strategies for faster retrieval from large datasets.

Key Technologies

  • Python, SQL, pandas, Apache Spark, and Faust
  • PostgreSQL and Cassandra
  • Psycopg and Cassandra CQL Engine

Customer Service Solution Architecture

I developed a secure, cloud-based voice solution using AudioCodes Virtual Edition SBC integrated with Microsoft Teams. The system enabled scalable customer-support communications through Direct Routing.

Microsoft Teams and SBC integration

Architecture and Integration

  • Designed a hybrid framework that securely routed voice traffic between AudioCodes VE SBC and Microsoft Teams.
  • Defined Azure infrastructure and networking requirements for reliable voice integration.
  • Provisioned the required Microsoft Teams licenses, users, and voice-routing policies.
  • Configured AudioCodes VE SBC as a Microsoft Teams Direct Routing interface.
  • Secured SIP trunking with TLS and SRTP encryption to protect voice traffic.

Key Technologies

  • AudioCodes Virtual Edition SBC
  • Microsoft Teams Direct Routing and Phone System
  • Microsoft Azure virtual networks and virtual machines