Data Engineer with python and date
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Data Engineer (Python | Snowflake / Databricks)
Role Summary:
We are looking for a skilled Data Engineer with strong expertise in Python, data processing, and modern cloud data platforms like Snowflake or Databricks. The role involves building scalable data pipelines, enabling analytics, and supporting data-driven decision-making across the organization.
Key Responsibilities:
- Design, build, and maintain scalable data pipelines (ETL/ELT)
- Develop data workflows using PythonWork with large datasets in structured and unstructured formats
- Implement data solutions using Snowflake or Databricks
- Optimize data pipelines for performance, reliability, and cost
- Build and manage data models, data marts, and data lakes
- Integrate data from multiple sources (APIs, databases, streaming)
- Ensure data quality, governance, and security
- Collaborate with data analysts, scientists, and business teams
- Automate workflows using orchestration tools (Airflow, etc.)
Required Skills & Experience:
Programming & DataStrong proficiency in Python
Experience with:
- Pandas, NumPy, PySparkSolid understanding of:
- Data structures & algorithms
- Data processing techniques
- Data Engineering
- Hands-on with:
- ETL/ELT pipeline development
- Data warehousing concepts
- Batch & streaming data processing
- PlatformsExperience with at least one:
- Snowflake
- DatabricksKnowledge of:
- Delta Lake (for Databricks)
- Snowflake features (streams, tasks, warehouses)
- Databases
- Strong SQL skills
- Experience with:
- Relational DBs (PostgreSQL, MySQL)
- NoSQL (MongoDB – optional)
- Cloud (Preferred)
- Experience in:
- AWS (S3, Glue, Redshift)
- Azure (ADF, ADLS)
- Google Cloud Platform (BigQuery)
- ToolsApache Airflow / Prefect
- Git, CI/CD pipelines
- Docker (good to have)
- Experience3–8+ years in Data Engineering or similar role
Certifications:
- (Optional But Valuable)
- Snowflake SnowPro Certification
- Databricks Certified Data EngineerAWS / Azure Data certifications
Nice To Have:
- Experience with real-time streaming (Kafka, Spark Streaming)
- Knowledge of data governance & catalog tools
- Exposure to Machine Learning pipelines
- Understanding of data security & compliance
- Soft SkillsStrong analytical and problem-solving mindset
- Ability to work with cross-functional teams
- Clear communication and documentation skills
- Typical Use Cases In This Role
- Building data pipelines for analytics dashboards
- Supporting ML models with clean, structured data
- Migrating legacy data warehouses to cloud platforms
- Creating scalable data lake architectures