You will get a Databricks data pipeline with Delta Lake for your business
Project details
Inconsistent, unstructured data costs your business time and trust. I build end-to-end data pipelines inside the Databricks Lakehouse that take your raw data and turn it into clean, reliable, query-ready assets.
Using Delta Lake for versioned, reliable storage and Databricks Workflows for orchestration, I handle everything from ingestion to transformation to delivery, it is built to run automatically and hold up in production.
What I handle inside the pipeline:
Raw data ingestion from files, databases, or APIs
Cleaning and transformation (nulls, duplicates, type mismatches, schema inconsistencies)
Delta Lake table creation with proper partitioning and schema enforcement
Workflow scheduling and orchestration via Databricks Workflows
Final structured output ready for dashboards, reporting, or downstream models
You get clean data, a documented pipeline, and a workflow that runs without babysitting
Using Delta Lake for versioned, reliable storage and Databricks Workflows for orchestration, I handle everything from ingestion to transformation to delivery, it is built to run automatically and hold up in production.
What I handle inside the pipeline:
Raw data ingestion from files, databases, or APIs
Cleaning and transformation (nulls, duplicates, type mismatches, schema inconsistencies)
Delta Lake table creation with proper partitioning and schema enforcement
Workflow scheduling and orchestration via Databricks Workflows
Final structured output ready for dashboards, reporting, or downstream models
You get clean data, a documented pipeline, and a workflow that runs without babysitting
Database Type
MySQL, MS SQL, Oracle, SQLite, PostgreSQL, MongoDB, Couchbase, Teradata, Realm Database, Azure Cosmos DB, LevelDBWhat's included
| Service Tiers |
Starter
$50
|
Standard
$150
|
Advanced
$300
|
|---|---|---|---|
| Delivery Time | 3 days | 5 days | 8 days |
Number of Revisions | Unlimited | Unlimited | Unlimited |
Source Code | - | - | - |
Optional add-ons
You can add these on the next page.
Fast Delivery
+$20 - $50Frequently asked questions
About Abdullateef
Data Engineer | Databricks Data Engineer | Big Data
Oyo, Nigeria - 4:20 pm local time
One of my core strengths is building streaming ETL pipelines using Spark Structured Streaming, where I detect anomalies and suspicious patterns in financial data as they happen, not hours later in batch processing.
What I do best:
1. Real-time data streaming pipelines (Databricks / Spark Structured Streaming)
2. Fraud detection systems using rule based anomaly detection
3. Data cleaning & transformation at scale (PySpark)
4. Handling missing, invalid, and inconsistent financial data
5. Building data warehouse-ready datasets (Delta Lake / SQL layers)
6. Designing robust ETL pipelines (bronze → silver → gold architecture)
Recent work highlights:
1. Built a real-time fraud detection pipeline on Databricks
2. Processed streaming transaction data with low latency anomaly detection
3. Reconstructed missing financial fields using business logic (Quantity, Total Spent, Price Per Unit relationships)
4. Designed a dual-layer system separating clean and suspicious transactions for auditing and analytics
Tools & Technologies:
Databricks, PySpark, Spark Structured Streaming, Delta Lake, SQL, Python, Data Warehousing, ETL Pipelines. I focus on building production-style, scalable, and maintainable data systems that can support real business decision-making especially in finance, analytics, and transactional systems.
If you need a Data Engineer who can go beyond batch ETL and build real-time intelligent data pipelines, I can help.
Steps for completing your project
After purchasing the project, send requirements so Abdullateef can start the project.
Delivery time starts when Abdullateef receives requirements from you.
Abdullateef works on your project following the steps below.
Revisions may occur after the delivery date.
Review
Review the source data, confirm requirements, and align on the expected output before any work starts
Data Ingestion
connect to the data source and load raw data into a landing/staging layer in the Databricks Lakehouse