Hi, I'm

Alfred Johnson

Data Engineer

Senior Engineer with 14 years of experience building high-scale integrations and production-grade data pipelines across fintech, telecommunications, and retail.

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About Me

Transforming complex data into
strategic business value

Senior Engineer with 14 years of experience, including 6+ years in data engineering across the fintech, telecommunications, and retail sectors.

Proven track record in designing & developing high-scale integrations and production-grade data pipelines to transform complex global data into strategic business value.

Get in Touch
Toolbox

Core Competencies

Languages

Python PySpark PySQL Java SQL

Platforms & Frameworks

Azure Databricks Apache Spark AWS Redshift AWS Lambda Azure APIM Azure Functions Mule ESB Spring Boot UiPath RPA

Database Systems

PostgreSQL Oracle MySQL ElasticSearch

Data Processing

Apache Flink Apache Kafka

Storage & Formats

Delta Lake Apache Iceberg Parquet CSV JSON XML

Data Modeling

Dimensional Modeling Kimball Methodology Medallion Architecture

Governance & Ops

Unity Catalog Collibra Airflow Azure DevOps Jenkins Git

Protocols

REST gRPC SOAP GraphQL WebSockets MCP SFTP Protobuf TLS/SSL OAuth OIDC SAML ISO 8583

Stakeholder Management

Requirement Elicitation KPI Alignment SLA/SLO Definition Strategic Roadmapping Expectation Management

Team Management

Cross-functional Collaboration Agile / Scrum Jira & Confluence Technical Mentorship
Work

Featured Projects

End-to-end data engineering projects built on real housing market datasets.

01

Singapore HDB Resale Price Pipeline

End-to-end ELT pipeline ingesting Singapore HDB resale flat transaction data from data.gov.sg. dbt models power price trend analysis by town, flat type, and storey range, with automated Airflow DAGs for daily refreshes.

  • Python
  • dbt
  • BigQuery
  • Airflow
View on GitHub
02

Australian Housing Market Analytics

Batch pipeline processing Australian property sales data, building a lakehouse with dimensional models to track median prices, days-on-market, and affordability metrics across states. Enables historical trend analysis at suburb level.

  • Spark
  • Snowflake
  • dbt
  • Airflow
View on GitHub
03

Housing Data Quality Framework

Automated data quality and anomaly-detection framework built across both Singapore and Australian housing datasets. Catches schema drift, outlier prices, and missing postcodes before they reach the warehouse — reducing bad data incidents.

  • Great Expectations
  • Python
  • PostgreSQL
  • Airflow
View on GitHub
Get In Touch

Let's work together

I'm open to new data engineering roles, freelance projects, and collaborations. Drop me a line and I'll get back to you promptly.

hirealfred@gmail.com