You will get Data Engineering: Data Quality & Governance Pipelines
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Data Engineering: You will get pipelines focused on data quality, data governance, and compliance with standards. As an experienced Data Engineer, I design and implement data engineering workflows that enforce validation, auditing, anomaly detection, and consistency across your data warehouse. Using Python and Airflow orchestration, I build automated ETL pipelines that manage schema changes and ensure clean, trusted data integration.
Cloud platforms such as Snowflake, Databricks, and BigQuery are optimized with best practices in database design and data modeling, ensuring long-term performance and scalability. Integrated with Power BI or Tableau, the solution delivers accurate analytics, transparent reporting, and actionable insights for decision-making.
With expertise as a Data Engineer in Python, SQL, and enterprise-grade data engineering, I help businesses remain compliant while maintaining high-quality, trusted data. My approach combines automated ETL pipeline development, optimized data warehousing, and governance frameworks that unify API integration, legacy systems, and cloud infrastructure, creating a scalable, future-proof foundation for growth and compliance.
Cloud platforms such as Snowflake, Databricks, and BigQuery are optimized with best practices in database design and data modeling, ensuring long-term performance and scalability. Integrated with Power BI or Tableau, the solution delivers accurate analytics, transparent reporting, and actionable insights for decision-making.
With expertise as a Data Engineer in Python, SQL, and enterprise-grade data engineering, I help businesses remain compliant while maintaining high-quality, trusted data. My approach combines automated ETL pipeline development, optimized data warehousing, and governance frameworks that unify API integration, legacy systems, and cloud infrastructure, creating a scalable, future-proof foundation for growth and compliance.
Database Type
MySQL, MS SQL, MS Access, SQLite, PostgreSQL, MongoDB, Teradata, LevelDBWhat's included $10,000
These options are included with the project scope.
$10,000
- Delivery Time 20 days
- Number of Revisions 1
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AG
Anna G.
Nov 4, 2025
Senior Data Engineer – ETL Pipelines & Snowflake Data Warehouse
Great collaboration overall. Strong expertise in building and optimizing ETL pipelines for Snowflake. Communication was clear and proactive, all deliverables were well-documented and delivered on time. Would definitely recommend.
MC
Moiead C.
Apr 21, 2025
RPA Engineer - Contractor
EK
Emil K.
Nov 10, 2021
QR code Photo Booth
Freelancer has been attentive to our needs and wishes during the process and has given valuable input themselves to help create a better product.
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CJ L.
Jul 20, 2021
Scrape multiple websites and dedupe + verify data
BWT has been a joy to work with. From scoping to kickoff, rounds of feedback, and final delivery, they've been patient, thorough, and an overall pleasure to work with. I would highly recommend working with them and they are going to be on my shortlist long-term.
SD
Suresh D.
Feb 26, 2021
Looking for an experienced Python developer with primary focus on web scraping.
About Oleg
Python Data Engineer | Data Scientist | Data Visualization Expert
100%
Job Success
Zaporizhzhia, Ukraine - 7:42 pm local time
As a Python Data Engineer, I specialize in designing scalable data systems. My role as a Data Engineer is focused on building reliable pipelines, automation, and analytics infrastructure. Every Python Data Engineer decision I make is oriented toward scalability, performance, and data reliability.
I work as a Python Data Engineer on enterprise-grade systems where architecture matters for both ingestion and transformation layers. As a Data Engineer, I ensure that raw data becomes structured, usable, and ready for business intelligence.
Here’s how I support our clients as a Python Data Engineer:
✅ Our ETL pipelines process over 100 million records monthly across major cloud data warehouses
✅ My solutions reduce manual reporting effort by up to 80% through end-to-end automation
✅ We build Python Data Engineer workflows for integrating and transforming complex datasets
✅ Every pipeline is tested and quality-checked to meet enterprise data standards
🔁 What I Do as a Python Data Engineer
⚙️ Data Engineering (Python Data Engineer Core Work)
🔹 API & event-based ingestion using Python Data Engineer best practices
🔹 Python + SQL transformations
🔹 Data modeling, schema design, enrichment
🔹 ETL/ELT into Snowflake, Databricks, BigQuery with Python Data architecture
🔹 Monitoring, retries, observability & data quality testing for Python Data pipelines
🔹 CI/CD for pipelines & cloud cost optimization as a Python Data Engineer
Platforms I’ve delivered as a Python Data Engineer process 100M+ records/month, integrate 30–80+ APIs, and power real-time BI environments.
📊 Data Visualization & BI (Python Data Engineer Perspective)
🔹 I bridge raw data with business decisions as a Python Data Engineer
🔹 Power BI, Looker Studio & Tableau dashboards connected by Python Data Engineer pipelines
🔹 Executive KPI reporting built by a Python Data Engineer
🔹 Semantic layer & metric standardization in Python Data Engineer systems
🔹 Real-time reporting (<5 min latency) enabled by Python Data Engineer architecture
🔹 BI performance optimization from a Python Data Engineer point of view
🔹 Data storytelling for leadership & operations powered by Python Data Engineer workflows
My solutions as a Python Data Engineer reduce manual reporting effort by up to 70-80% and significantly improve forecasting accuracy.
🧩 Recent Experience (Python Data Engineer Projects)
🔹 Retail & eCommerce Data Warehousing (Python Data Engineer)
Built ingestion + normalization pipelines for 120+ eCommerce sources, syncing ~500K SKUs/day into Snowflake / BigQuery using Python Data Engineer architecture.
🔹 FinTech Ingestion & Reporting Layer (Python Data Engineer)
Delivered automated pipeline pulling from 30+ sources (APIs, DBs, files), built with Python Data Engineer logic for validation, transformation, and reporting.
🔹 Government ETL & Document Processing (Python Data Engineer)
Automated processing of 10K+ documents/day using Python Data Engineer workflows: extraction, classification, mapping, and database loading.
🔹 Healthcare Data Normalization & Compliance (Python Data Engineer)
Cleaned millions of records using Python Data Engineer pipelines with schema mapping, PII-aware handling, and reproducible transformations.
🔹 Large-scale Cloud Migrations (Python Data Engineer)
Migrated legacy systems into BigQuery/Snowflake using Python Data Engineer architecture with incremental loads and automated pipelines.
💻 Tech Stack (Python Data Engineer Toolkit)
⚙️Languages: Python, SQL, DAX, Power Query, PySpark, Scala, Bash/Shell, JavaScript, etc.
⚙️Data Engineering & Processing: PySpark, dbt, Airflow, Prefect, CDC, REST & GraphQL, etc.
⚙️Data Warehouses & Databases: Snowflake, Databricks, BigQuery, AWS, PostgreSQL, MSSQL
⚙️Cloud Platforms: AWS: S3, Glue, Lambda, CloudWatch, Athena, Redshift, BigQuery, Dataflow
⚙️Data Modeling & Architecture: Star schema, Snowflake schema, Lakehouse architecture, etc.
⚙️Monitoring & Data Quality: dbt, Prometheus, Grafana, AWS CloudWatch, GCP Monitoring, etc.
⚙️BI & Visualization: Power BI (Desktop, Service), Tableau, Looker Studio, Metabase, etc.
⚙️DevOps & CI/CD: Git, GitHub, GitLab CI, Docker, Terraform, etc.
🚀 If you need automated pipelines, clean data models, and executive-level dashboards - as a Python Data Engineer I can help you build a robust system from end to end.
➡️ Invite me to your job and let’s design a scalable data strategy with a Python Data Engineer leading the way.
Last updated June 15, 2025
Steps for completing your project
After purchasing the project, send requirements so Oleg can start the project.
Delivery time starts when Oleg receives requirements from you.
Oleg works on your project following the steps below.
Revisions may occur after the delivery date.
Requirements & Compliance Audit
Review current data systems, governance requirements, and compliance standards to define pipeline goals.
Architecture & Governance Strategy
Design data engineering workflows with validation, auditing, anomaly detection, and quality enforcement.