Headline

Data Engineering, Cloud & BigData Leader | @Loyalty Methods, ex-(Cloudera, Bombora, HearstAutos, Coforge, Infosys); ASU, USA.

About

Hi, I’m Narayana Motamarri (NaMo) 👋 Data Engineering Leader (Head / Director / Manager) with 18+ years of experience building large-scale Cloud based Enterprise data platforms across AWS & GCP. Managed / Mentored teams of 30+ across Data Engineering, Analytics, Data Science, DataQA, BI & AI. Designed & Migrated data ecosystems, Architect & Built ETL pipelines, real-time (low latency) ad-serving insights through cost-optimised Architectures enabling Data Governance, Data Catalog, Metadata & Observability. Key Achievements: 1. Working on various enterprise data use-cases at product & service based companies like Loyalty Methods, Bombora, Coforge catering to wider group of enterprise customers. (2021 - Present) 2. Built Hearst Autos’ AWS cloud enterprise data platform from the ground up (Redshift, Glue, EMR, Spectrum, DMS, etc.) — 7.5 years of scale, reliability, & innovation. (2014 - 2021) 3. Achieved my dream of working at Cloudera. contributed towards Hadoop-based bigdata applications. (2012 - 2014) 4. Completed a research-intensive MS at ASU, involving large-scale analytics using Hadoop. (2009 - 2011) 5. Campus placement: One of only 2 students placed first at Infosys Technologies Ltd from my B.Tech IT class of 60. (2007) 6. Awarded “Best Outgoing Student” in 10th grade for excellence across academics, co-curricular & extracurricular activities. (2001) My expertise spans over: Big Data & Analytics • Redshift, BigQuery (MPP/Columnar) • Spark (Databricks, AWS Glue) • Hadoop (Cloudera, AWS EMR) • Snowflake Cloud Platforms • AWS • GCP Core Areas • Data Engineering • Data Lakes & Data Warehouses • Data Analytics, BI, AI & Observability • Data Catalog, Metadata & Data Governance • Low Latency Insights (GCP Bigtable) I’m certified as, • Cloud Analytics Master & • Cloud Analytics Architect, from Cloud Analytics Academy (Snowflake + AWS). GitHub: github.com/narayanM Twitter: @NarayanGupta Currently, I’m part of Loyalty Methods Inc. Previously, I worked at Coforge working on PMI’s data platform & prior to that at Bombora, building real-time visitor insight systems on GCP Bigtable. Before that, I scaled & modernized Hearst Autos’ AWS Redshift data platform, end-to-end pipelines, ingestion, materialized views, KPI reporting, data lake (Spectrum), Docker/ECS—later migrating the full stack to GCP (Airflow/Composer, BigQuery). Earlier roles include engineering positions at Cloudera, MedTrust, and Infosys. My Master’s Thesis: “Large Scale Analytical Insights of Email Communication Patterns” (ASU) Repository: http://repository.asu.edu/items/9485

Location

Hyderabad

AI stack

antigravity

cursor

claudecode

Work experience

Data Engineering Manager at Loyalty Methods, May 2024 - Present · 2 yrs 4 mos, Hyderabad, Telangana, India, • Owned delivery of the RCX (Reactor-CX) data platform providing Analytics to enterprise customers. • Managed & scaled a 30+ member team owning roadmap, delivery & execution quality. • Re-Architected ETL state management using AuroraDB improving ETL performance by 55%. • Reduced Redshift cloud DW costs by 37% by right-sizing node types & leveraging reserved pricing. • Executed evolution of RCX data product from v3.23 → v4.6, coordinating cross-functional teams. • Introduced AI-assisted development by integrating IDEs with Claude & DeepSeek Coder APIs, reducing PR turnaround time & improving code review throughput. • Overseen onboarding & implementation of new enterprise customers, owning data migration, data profiling, mapping, validations ensuring smooth go-lives. stack: Redshift (DW), Pentaho / PDI (ETL), AuroraDB, PBI & QuickSight, PyCharm, Claude, DeepSeek.

Data Architect at Coforge, Aug 2023 - Apr 2024 · 9 mos, Hyderabad, Telangana, India, • Delivery of Financial Data Analytics for a European Retail giant (PMI: Philip Morris International). • Engineered ETL pipelines of Finance data assets from SAP to Snowflake using AWS Glue. • Managed & Mentored a cross-functional team of 20+ (Data Engineers, Data Analysts, Data Scientists, Data-QA, DevOps). stack: Snowflake-DB, AWS Glue, PBI, Data Vault Modeling (hubs, links, satellites), S3.

Data Engineer IV at Bombora, Sep 2021 - Mar 2023 · 1 yr 7 mos, San Francisco Bay Area, • Engineered Bombora’s low latency (100ms) ad-serving Insights of its Intent & Identity data. • Led development of Airflow DAGs (orchestration layer), improving ad-serving reliability. • Collaborated on GCP BigTable Infra (multi-region) setup reducing query latency. • Engaged with vendors to evaluate & onboard new platforms & tools as per team requirements. stack: Airflow2.3 (DAGs), GCP (BigTable, BigQuery, Dataflow, GCS

Data Architect at Hearst Autos, Apr 2020 - Sep 2021 · 1 yr 6 mos, San Francisco Bay Area, Led Hearst Autos Data initiatives while collaborating efforts with other leads from other divisions like *Hearst Magazines* and *CDS Global* (a Hearst Company) to consolidate multi-cloud landscape Migrated AWS based DW, DL & pipelines to GCP ( BigQuery, GCS, Composer (Airflow)).

Lead Data Engineer (Container-ization) at Hearst Autos, Jan 2019 - Mar 2020 · 1 yr 3 mos, San Francisco Bay Area, Jumpstart Automotive Media is re-branded as Hearst Autos (a subsidiary of Hearst). Architect JAM's / HA’s • Data Warehouse: Redshift (MPP) (Scale out) (12 Node 24 TB) Data Lake: Redshift Spectrum (100 TB) • Data Pipelines (Ingestions, Materialized Views, Stored Procedures & KPI Reports) • Workflow Go-to person for BigData, Data Integration needs • Completed AdServer migration in 40 days. I.e. update all Data Pipelines and processes to work with new AdServer. Done with no external impact to clients/customers • Completed Docker/Container-ization of data center based entities/processes in a single quarter. For complete picture, Continue below

Sr Data Engineer (BigData & AWS Cloud) at Hearst Autos, Mar 2014 - Dec 2018 · 4 yrs 10 mos, San Francisco Bay Area, Duties: 1. • Design, Implement & Automation of *DataPipelines* (ETL/ELT)(data ingestion)(MaterializedViews) Stack: Redshift, Glue(PySpark), Spectrum, S3, GCPBucket, PostgreSQL, Python, Bash, EMR (Saved $$) • 13 pipelines. Trigger subprocesses on Thresholds, wait for file arrival, handle n/w & operational errors et al • AdServer/AdExchange Data, Viewability & AdQuality Data, Sales Data, et al 2. • Implementation & Automation of the *KPI Reports*, designed by Analysts for ext & int clients • 25 KPI reports Ad Campaign KPI, Car Shopping Behavior, Revenue share KPI, et al 3. • Design & Development of Redshift. Perform query & schema Optimizations • 12node 24TB Redshift DW & 100TB S3/Spectrum DataLake • Oversee Redshift Operations for a stable & reliable cluster, by *Vacuum/Analyze* & *WLM* Configs + Work with AWS SAs for Redshift health checks + Provide feature requests to new services: Spectrum, Glue, ETLeap, et al 4. • Design & Implementation of *Workflow* to ensure dependencies btwn Ingestions/MaterialisedView/Reports Stack: Bash (to trigger SAS & processes behind VPC/Bastion-Host) Others: -> Migrations & Transitions * Redshift Region (West->East) * Redshift Node-type (SSD->HDD) * AdServer (DFP) with ever changing business needs * Docker/Containerization -> Empowered & Mentored with Redshift 101s. Trained 3 Analysts with RedshiftSQL and 2 with Bash -> Evolved JAM's data ecosystem by + integrating Legacy (SAS/BI) data to Redshift using DMS & by + enabling New services: Spectrum, Glue, et al -> Built & Maintain ~9000 LoC & 90 pages of docs Summary: Lead the Development of JAM's Data Platform from *ground up* Highlights: -> Proposed upfront a high performing, cost effective (1/10th), easy operational DW & implemented it (Saved $$) -> Run the Data Engineering at Cost affective way (Saved $$) -> Played an active role in replacing 3rd party analytics providers with in-house reports (Saved $$)

Data Science Developer at Cloudera, Aug 2012 - Feb 2014 · 1 yr 7 mos, Palo Alto, CA, I was part of the founding team of *Cloudera's CCP: Data Scientist* certification program (hands-on), which successfully rolled out the first installment of the Data Science hands-on certification. And have certified few successful candidates. Collaborated in developing simulated dataset. Built and Automated testing process to evaluate end user code for scalability. Handed out training/sample-solutions for next installment.

Education

Master of Science, Computer Science, Arizona State University

Bachelor of Technology, Information Science and Technology, Velagapudi Ramakrishna Siddhartha Engineering College

Public links

github: https://github.com/narayanM