Waqas (Wes) Shah

At Bunnings, I played a pivotal role in the Data Engineering team, collaborating on the development and orchestration of batch jobs to ingest complex data from diverse sources. My expertise in leveraging cutting-edge technologies like Airflow and a powerful metadata-driven framework helped streamline our data pipeline process, delivering actionable insights and facilitating data-driven decision-making.

Client: Telstra

Project: Customer Interaction Journey (Consumer) and Project Grow (Enterprise)

Role: Insights Manager

March 2020 - Present

Telstra's initiative to improve customer (Consumer and Enterprise) experience via targeted communications based on the data points relating to customer behavior; captured in disparate systems, consolidating the information and configuring them in a suite of applications to deliver campaigns through various channels.

Achievements: Consumer Domain:

• Contributed to a highly scalable data model for consumers in AWS Redshift comprising of various data domains such as Customer, Products, Services, Usage and Account Info
• Successful launch of high revenue generating marketing, services and regulatory use cases targeting various customer segments based on socio-economic factors through Omni channel
• Learned and adapted quickly to new technology and software applications.

Enterprise Domain:

• Assisted in generating quality leads by working closely with the sales and marketing teams that resulted in higher conversion compared to FY21
• Collaboratively introduced data driven insights based approach on identifying cohorts across various industries and wallet share as opposed to product and offer launch and then thinking about the potential cohort (mindset shift)

Responsibilities:

• Managed onshore and offshore teams by allocating tasks and monitoring the progress using Atlassian suite
• Conducted workshops to capture the customer journey to identify the customers and channels through for communication (SMS, Email, Digital, NBA)
• Liaised with the marketing team to capture the business requirements and eligibility rules for feature engineers to develop new features
• Designed new solutions (future state) and presented various approaches to enhance existing solutions (current state)
• Conducted proof of concepts to apply proposed solutions in real world to gain insights and measure the impacts
• Identified gaps in data and engaged with the relevant source system teams to import the missing data with the help of data engineers
• Presented insights to the Telstra leadership to facilitate future campaign offers and higher revenue generation in certain industries

Client: Cbus Super

Project: Cloud Platform Design and Enhancement

Role: Senior Data Engineer

Aug-2019 – March 2020

Cbus Super underwent a massive uplift from legacy to a complete end to end cloud based transformation.

• Presented updates in daily stand-ups with suggestions to overcome potential roadblocks where applicable
• Tracked project progress and deliverables through Jira user stories
• Documented process to train staff to manage platform operations to meet SLAs
• Led multiple technical streams of work to unify the data in the data lake and then propagated to managed and operational data stores for reporting and visualisation (Jenkins, S3 Data Lake, Glue, Redshift, Tableau)
• Designed and implemented solutions to enhance the cloud ecosystem to process streaming data to ensure operational assurance (Kinesis Firehose, CloudWatch, Lambda)
• Developed config driven ETL jobs by designing and implementing metadata store (RDS, SSM, Talend, Bitbucket)
• Performed current state analysis to increase efficiency for highly available transient EMR clusters for CDC (VPC, Subnets)
• Liaised with business to capture and document requirements (Confluence), propose options and recommendations
• Designed and implemented NoSQL data store (DynamoDB) for maintaining reference data hub to provide downstream applications with near real-time access

Client: NBN Co

Project: Data Capability Uplift,

Role: Data Modeller

Oct-2018 – July 2019

• Led data acquisition and transformation tasks for migrating data from on-premise data warehouse to Cloud
• Built data ingestion pipeline using EC2 instances and batch file for the initial phase of the program to keep the cost to minimum
• Applied best practices to store data in Cloud. This resulted in quick access to centralised data to the executive and provided self-service to enable the management to track headline, business critical metrics
• Liaised with the SMEs, product owners and stream leads to capture the business requirements
• Led migration of data from on-prem IBM Netezza to Amazon Redshift using SQL, EC2 instance and Amazon S3 bucket
• Led conversation on solution design, data modelling, and development of the use case for the business stakeholder
• Developed tableau data source MVP for business to interact and incorporate feedback

Responsibilities:

• Assisted manager in executing project and drafting project management documents
• Collaborated with cross functional teams to capture requirements
• Designed and developed databases for testing and production environment
• Developed dashboards and reports for Principals using Tableau

Achievements:

• Reduced cost of operations by roughly 15% in a year by moving to cloud

Technologies used:

• Amazon EC2 - MS SQL Server
• Amazon S3
• Tableau

Responsibilities:

• Supported in answering business imperatives by developing SQL code for PostgreSQL MPP system
• Worked under lean BI mythology to deliver quick and meaningful results
• Developed multiple reports to track motor vehicle claims lodged vs claims granted in Tableau

Achievements:

• Identified fraudulent claims by understanding business rules
• Brought two isolated business units to work in cohesion

Responsibilities:

• Captured and documented business requirements
• Developed ETL scripts to load data to financial andcation
• Developed ETL scripts to load data to financial and communication data models
• Developed reports and dashboards in Tableau

Achievements:

• Delivered smart solutions in timely fashion to telecom and financial sector clients
• Enabled business user to carry out self-service reporting
• Successfully reconciliated revenue generating data streams
• Improved data quality and representation of figures