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I will build scalable etl pipelines using python or pyspark
Indien
From Data Chaos to Clarity, Done Right the First Time
Über diesen Service
Are you drowning in messy data or struggling to move data between systems?
Let me help you with a clean, efficient, and scalable ETL pipeline using Python or PySpark.
Im a Data Engineer with 5+ years of experience in building robust data pipelines, cleaning millions of records, and automating workflows for startups, enterprises, and SaaS products.
What I Offer:
- Extraction from CSV, Excel, APIs, PostgreSQL, MySQL, etc.
- Data cleaning (null handling, duplicates, type casting, etc.)
- Business logic and transformation
- Load to PostgreSQL, Snowflake, BigQuery, S3, etc.
- Logging, error handling, and monitoring
- Scheduling with cron or Airflow
Tools & Tech:
- Python
- PySpark
- Pandas
- SQLAlchemy
- psycopg2
- Apache Airflow
- PostgreSQL
- Docker
FAQ
What do you need from me to get started?
I’ll need details like your data source (CSV, database, API, etc.), destination platform, sample data (if available), transformation rules, and any scheduling or orchestration requirements.
Can you connect to cloud databases or APIs?
Yes! I can connect to cloud platforms like AWS RDS, Google BigQuery, PostgreSQL, S3, and APIs using Python or PySpark.
Do you provide scheduling or automation for the pipeline?
Absolutely. I can set up cron jobs or Airflow DAGs depending on your environment and package selection.
Do you handle real-time or streaming data?
Yes, in the Premium package or as an extra, I can implement streaming pipelines using Kafka, Apache NiFi, or similar tools.
Will the code be reusable and documented?
Yes, every package includes clear documentation. Standard and Premium packages include structured README files, config instructions, and even flow diagrams.
What if I don’t know the exact transformation logic yet?
No worries! I can help you define it based on your use case and guide you through refining your logic before development.
Can I get revisions if something doesn’t work as expected?
Definitely. Each package includes revisions, and you can add more if needed. I strive for full satisfaction.

