Strategic, solutions-oriented Software Architect with 11.5 years across high-scale data engineering, big-data cloud analytics, and quality engineering frameworks.
Designs and deploys enterprise-grade data landscapes on Azure, Databricks, Snowflake and Apache Spark managing clusters that crunch billions of operational rows. Steers cross-functional modernizations from legacy infrastructure to native cloud, mentors technical groups of 14+ engineers, and delivers executive-level analytics for international telecom conglomerates.
Native Azure ecosystems — landing zones, integration patterns, secure data plane.
Databricks, Snowflake, Cloudera, Hadoop and Apache Hive at billion-row scale.
Apache Spark and PySpark cluster sizing, pipeline tuning and cost-aware optimization.
Advanced SQL, Python and shell scripting for production-grade pipelines and tooling.
Tableau dashboards engineered for C-suite stakeholders and regulatory reporting.
CRM, OMS and core telecom flows — international BSS & subscriber lifecycle.
Career spent at Amdocs, working with the world’s most demanding telecom operators — from QA engineer to data engineering team lead to architect.
Promoted to map technical governance, architectural roadmap, and platform standards across enterprise data units. Oversees multi-phased engineering for reliable, decoupled, secure cloud-native environments.
Led a 7-engineer squad managing 600+ relational tables and 400+ daily vendor extracts to 50+ international downstream channels on Azure, Databricks and Snowflake. Owned 40+ Tableau executive reports built on multi-billion-row telecom streams.
Pivoted from QE to Data Engineering via internal job posting; led 7 developers across multi-tenant big data hosting for 3ROI’s subscriber base — 300+ analytical schemas, hybrid on-prem Cloudera Hadoop and Azure with heavy Spark/PySpark workloads.
Built modular automation and regression layers for CRM portals and customer-facing web flows, and authored the in-house D3 utility (Design, Data, Deliver) for dynamic test modeling and synthetic data generation.
Functional validation of complex Order Management Systems, ensuring system uptime and clean database persistence under heavy peak loads.
Started in the AQE division validating end-to-end e-commerce flows for AT&T’s online store and embedded regression automation into CI pipelines to remove delivery bottlenecks.
A small slice of the operators whose subscribers I’ve helped serve at Amdocs.
Production-grade data engineering on Databricks — Lakehouse architecture, Spark optimization, governance.
Azure-native data integration, transformation and serving with ADF, Synapse and Databricks.
Drop your next certification here.
Tarun’s grasp of large-scale data architectures is rare and refreshing — he turns complexity into something a steering committee can act on.
He turned a fragile, multi-vendor legacy pipeline into a textbook cloud-native platform — and made it look easy.
If you want execution and clarity in the same package, you want Tarun on the team.
— Kent Beck