Data Engineer
Service Description
Professional Data Engineer | ETL Pipelines | Dashboards | Cloud Solutions
Description:
I am a dedicated Data Engineer specializing in transforming raw data into actionable insights through clean, efficient, and scalable solutions. With expertise in ETL pipelines, SQL databases, dashboards, and cloud architecture, I help businesses make data-driven decisions and optimize their workflows.
What I Offer:
ETL & Data Pipelines: Design, build, and maintain robust pipelines for ingesting, transforming, and storing data.
Data Cleaning & Transformation: Ensure high-quality, structured data ready for analysis.
Dashboard & Reporting: Interactive dashboards in Power BI, Tableau, or Excel to visualize KPIs, trends, and metrics.
Cloud Data Solutions: Support for cloud platforms like AWS and scalable architecture for data processing.
Database Management: SQL, PostgreSQL, MySQL optimization and query solutions.
Automation & Workflow: Streamline processes using Python, Airflow, and cloud integrations.
Certifications & Skills:
IBM Data Engineering Professional (Coursera)
AWS Cloud Solutions Architect (Coursera)
Python, SQL, Power BI, Tableau, AWS
Why Choose Me:
Clean, organized, and professional dashboards
Scalable and reliable data pipelines
Timely delivery with high-quality output
Custom solutions tailored to your business requirements
Let’s Work Together:
Whether you need a custom recruitment dashboard, sales analytics, ETL pipelines, or cloud-based data solutions, I can provide a professional and scalable solution. Share your requirements, and I will craft a solution that fits your business needs.
Technology Used
Technologies Used to Perform Scope of Work
To deliver high-quality, scalable, and efficient data solutions, I use the following technologies and tools:
1. Programming & Scripting
Python – Data manipulation, ETL automation, API integration
SQL (MySQL, PostgreSQL, SQL Server) – Data extraction, transformation, and query optimization
2. Data Pipelines & Workflow
Apache Airflow – Automated ETL workflows and scheduling
Docker – Containerization for reproducible environments
3. Data Visualization & Dashboards
Power BI – Interactive KPI dashboards and reporting
Tableau – Trend analysis and visualization
Excel (Advanced) – Pivot tables, charts, and reporting
4. Cloud Platforms
AWS – Data storage, pipeline deployment, and cloud architecture
Azure (Optional) – Cloud-based data integration
5. Additional Tools
Git & GitHub – Version control for code and project management
APIs & Data Connectors – Integration with external data sources
Frequently Asked Questions
Q1: What type of data projects do you handle?
I work on ETL pipelines, database design, data cleaning, interactive dashboards (Power BI, Tableau, Excel), and cloud-based data solutions (AWS, Azure). I also handle recruitment, sales, marketing, and performance analytics dashboards.
Q2: Do you provide customized dashboards?
Yes! I design dashboards completely from scratch according to your KPIs, branding, and business requirements. You will get a clean, interactive, and actionable dashboard.
Q3: Can you work with my existing data?
Absolutely. I can clean, transform, and integrate your existing data into dashboards or pipelines without altering the original data.
Q4: Which tools and technologies do you use?
I primarily use Python, SQL (MySQL, PostgreSQL), Power BI, Tableau, Excel, Apache Airflow, Docker, and cloud platforms like AWS and Azure.
Q5: Do you provide cloud solutions?
Yes, I design and deploy cloud-based data pipelines and dashboards using AWS services and other cloud technologies to ensure scalability and reliability.
Q6: Can I request changes after the dashboard/pipeline is delivered?
Yes, I provide support for adjustments and updates according to your requirements to make sure the solution fits your workflow perfectly.
Q7: What certifications do you hold?
I hold the following professional certifications:
IBM Data Engineering Professional (Coursera)
AWS Cloud Solutions Architect (Coursera)
Q8: How long will my project take?
The timeline depends on project complexity. Simple dashboards can take 1–3 days, while full ETL pipelines or large datasets may take 1–2 weeks. A clear timeline will be provided once requirements are shared.
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