Vivek Basavanth Hanagoji — Data Engineer

Who I Am

About Me

Name: Vivek Basavanth Hanagoji

Role: Data Engineer 2

Company: Kraft Analytics Group (KAGR)

Location: Boston, MA

Core Skills

SQL & Data Modeling95%

Python & PySpark90%

dbt & Kimball Modeling90%

Snowflake / Redshift / BigQuery88%

Airflow & Spark85%

Connect on LinkedIn

Data Engineer with 3+ years of experience designing distributed pipelines, cloud warehouses, and data quality frameworks across Python, SQL, Spark, Snowflake, dbt, and AWS. Currently at Kraft Analytics Group (KAGR) — building production fan engagement analytics for all NFL partner teams. Comfortable owning systems end to end, from raw ingestion through modeling to production dashboards.

ProfileData Engineering & Analytics
EducationM.S. Computer Software Engineering · Northeastern University
LanguagesPython, SQL, JavaScript, HTML/CSS
Cloud & DWAWS (S3, EC2, EMR, Glue, Athena) · Snowflake · Redshift · BigQuery · Azure Data Factory
Big DataApache Spark, SparkSQL, Hadoop, Hive
OrchestrationApache Airflow, Prefect, AWS Glue, Kubernetes, Talend, Alteryx
Data Modelingdbt, Kimball, SCD Type 1/2/4, ETL/ELT Design, Data Quality Testing
BI ToolsPower BI, Tableau, Looker Studio
InterestsTraveling, Travel Photography

0 + Projects completed

Career

Work Experience

Building production-grade data systems across sports analytics, enterprise telecoms, and the cloud.

Jun 2025 — Present

Data Engineer 2 Current

Kraft Analytics Group (KAGR) · Boston, MA

Architected multi-tenant fan engagement analytics by integrating unsubscribe activity into email export pipelines (Snowflake SQL, Python), enabling precise audience delivery across 8M+ contact records for all NFL partner teams.
Built a Python GraphQL ingestion layer from the Shopify API that unnested 5-level nested JSON, serialized to Parquet via PyArrow, cutting per-batch file size 77% (2.1GB → 480MB) before landing in AWS S3; eliminated 3M duplicates.
Engineered a 5-stage dbt lineage for an NFL client — flatten, Melissa API standardization, deduplication, and merge — version-controlled and deployed via CircleCI.
Authored dbt generic tests enforcing uniqueness and referential integrity, proactively catching 4 upstream schema breaks before they reached partner-facing dashboards.
Designed an anonymization match-pass for KAGR's multi-source identity resolution pipeline (Archtics, Shopify, Salesforce, Ticketmaster, StubHub, Lava), merging 1.5M dormant records into golden audience IDs.

Snowflake dbt Python GraphQL AWS S3 PyArrow CircleCI Shopify API Salesforce Ticketmaster

Jul 2019 — Feb 2022

Data Engineer

Vodafone Intelligent Solutions (VOIS) · Pune, India

Designed SQL-based data models in AWS Redshift enabling OLAP cube analysis for user behavior, transaction patterns, and fraud detection, powering 3 downstream analytical workflows.
Orchestrated daily batch ETL pipelines with Airflow and Spark, ingesting 70M+ rows (~1TB) per day of telemetry data into Redshift.
Implemented SCD Type 2 & Type 4 to track historical customer attributes; built Python validation routines achieving 99% data completeness.
Partnered with PMs and SDEs to design a secure, product-partitioned data lake optimized for Athena and Redshift queries.