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Senior Machine Learning Engineer / Data Scientist

Heicoders Academy

Instructor

Gojek

Data Scientist

Data Analyst

Kuprion Inc

R&D Assistant

Fave

Growth Planner

Nanyang Technological University

Research Assistant

Xfers

Marketing Analyst

🤖 I use analytics, machine learning and deep learning to fight spam content at work. Classic ML algorithms, time series analysis, natural language processing, or computer vision are just some examples of the techniques I’ve used.

🧑‍🏭 I like learning and teaching things! I'm a chemical engineer turned data scientist. I self-learnt pretty much everything to move into tech. I'm now pursuing my Master's in Computer Science, teaching at a data science bootcamp, and sharing data science knowledge online.

Let’s connect. 
Personal site: https://www.travistang.com
Email: travistang.vh@gmail.com

Travis Tang

Landal

Data Engineer

DocuSign

• Designed and implemented efficient data pipelines in Snowflake, utilizing dbt™ Cloud for data modeling and transformations to ensure data consistency and quality.
•  Proficient in Snowflake - Procedures, Functions, Views, SnowPipe, Stages, File format, Storage Integration, Internal and External Stage. 
• Worked on Dbt Cloud Packages, Macro, Incremental Models, Hooks, Seeds, YML Files, dbt Jobs, and Environmental Variables.   
• Orchestrated data workflows and scheduled tasks using Airflow
• Developed Python scripts to enrich customer data from various B2B data providers for Master Data Management.

Prescience Decision Solutions

Client: Landmark Groups
• Designed and implemented an end-to-end data pipeline using Azure Databricks for data transformation and Azure Data Factory for orchestration and scheduling, resulting in a 25% increase in data processing efficiency for large-scale business analytics.
• Mentoring the junior engineers and guiding the team members on the assigned tasks of migrating the SAS Analytics code to Pyspark code / Spark SQL using Azure Databricks and Azure Services

Principal Data Engineer

Client: Copia Kenya
• Researching, designing, and developing ETL and Data Pipeline components and visualization reports required for the analytical of the E-commerce domain
• Writing complex queries on PostgreSQL/ Redshift for the Data Pipelines and Reports
• Automated customer segmentation analysis for marketing activities using Python, pandas, and NumPy, resulting in a 63% increase in customer conversion rate
• Developed and optimized PySpark data processing pipelines for batch processing 
• Deploying the analytics code using AWS Services like Lambda, Glue, Spark, S3, Redshift, Cloud Watch
• Successfully implemented open-source software and tools for both internal use cases and client projects, resulting in a 20% reduction in budget

AWS cloud services: EC2,AWS RDS, Redshift , S3, Lambda, Step Function, Pyspark 
Azure  : Azure Data Factory, Azure Databricks , ADLS, Delta Lake
SQL and NoSQL databases - Postgres, Redshift, MySQL
Visualization Tool: Tableau, Knowi, Excel , Apache Superset

Senior Data Engineer

Tata Consultancy Services

• Proficient in SQL, Python, Shell Scripting, Linux , Java , Spark, SparkSQL, PySpark
• Part of Backend Product Development Team of TCS Customer Intelligence & Insights™ with main focus on Banking domain
• Successfully implemented various POC on Cost Optimization by using Open Source Software and Tools 
• Responsible for writing ETL Transformation query using Postgres SQL and Apache Spark 
• Designing Airflow DAG for ETL Workflow Orchestrations
• Jenkins and Data Archival Job Automation Scripts using Shell Script
•  Building data pipelines and integrating data from various sources, including structured and 
    unstructured data
• Data governance - Designing and implementing data governance policies and procedures, including GDPR and PII compliance for Datawarehouse 
• Implemented MLOps for the Banking Analytical Product using Apache Airflow , Shell Script , Python

Data Engineer ( TCS Digital )

• Proficient in SQL, Shell Scripting, Linux , Java, Message Queue (Kafka)
• Responsible for design and development of various data streaming solutions for the Banking and Large scale Enterprises
•  Proficient in configuring and managing message-oriented middleware systems such as IBM WebSphere MQ and Apache Kafka, ensuring reliable and scalable communication between distributed applications
• Experienced in setting up and managing message queues (WebSphere MQ) and topics (Kafka), including configuring triggers, channels, partitions, and consumer groups to optimize message processing workflows
• Data Streaming and Integration for the various B2B applications using Message Queue (MQ) and database adapters for the Fortune 500 Clients

Assistant System Engineer

Data Engineer with a strong background in Data Processing, Analytics, and Data Warehouse Management. Skilled in developing and implementing robust data pipelines, ensuring data consistency, and driving actionable insights for organizations. Proficient in a wide array of technologies and tools including Python, SQL, dbt Cloud,Apache Spark, and AWS/Azure services. Passionate about leveraging data-driven strategies to support business objectives and drive growth.

• Banking, Data Warehouse, Retail, Insurance, E-commerce, Logistics
• GenAI: LLM, Azure OpenAI , GitHub Copilot, GPT-4o, Llama, ChatBot, AI/ML Data Operations, 
• Data Streaming and Data Integration of B2B Applications 
• AWS, AWS Glue, S3, Lambda, Linux 
• Azure Data Factory, Azure Databricks, ADLS2
• Database: Postgres, MySQL, AWS RDS, MongoDB
• Data Warehouse:  AWS Redshift, Snowflake
• SQL, Python, Java, Shell Script, Google App Script
• Spark, SparkSQL, PySprak  Airflow, MQ, Kafka, Druid, CI/CD, Github, SVN, Jenkins, REST APIs, Docker
• ETL Tools: Airbyte, Talend (Open Source Version), dbt (data build tool), Fivetran
• Visualization tools: Tableau, Knowi, Apache Superset 
• Business and Data Analysis

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Travis Tang

Vijayakumar Z

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