Cialfo - Senior Data Engineer - Python/SQL

We are looking for a Senior Data Engineer with strong experience in building scalable data platforms, data pipelines, and backend data systems for high-volume production environments.

The ideal candidate should have hands-on expertise in Python, SQL, distributed data processing, cloud platforms, and modern data engineering practices. This role requires strong ownership of the data layer including ingestion, transformation, modeling, optimization, and reliable data delivery across systems.

Key Responsibilities :

- Design, develop, and maintain scalable ETL/ELT pipelines and data workflows.

- Build and optimize large-scale data processing systems using Python and SQL.

- Develop robust batch and real-time data pipelines for structured and unstructured datasets.

- Work with distributed processing frameworks such as Spark/PySpark and Kafka.

- Design and optimize data models, schemas, and warehouse structures.

- Ensure data quality, integrity, validation, and monitoring across pipelines.

- Optimize query performance, partitioning, indexing, and data storage strategies.

- Build and maintain REST APIs and backend data services where required.

- Work with cloud-native data platforms on AWS, Azure, or GCP.

- Collaborate with analytics, product, and engineering teams to deliver reliable datasets and scalable data solutions.

- Support CI/CD, deployment automation, and modern engineering best practices.

- Troubleshoot production issues, pipeline failures, and performance bottlenecks.

Required Skills & Experience :

- 5+ years of experience in Data Engineering or Backend Data Systems.

- Strong hands-on experience with Python and SQL.

- Experience working with Spark/PySpark, Kafka, and distributed data systems.

- Strong expertise in PostgreSQL, MySQL, or similar relational databases.

- Experience building scalable ETL/ELT pipelines and data workflows.

- Strong understanding of data warehousing, data lakes, and data modeling concepts.

- Experience with cloud platforms such as AWS, Azure, or GCP.

- Good understanding of API integrations and backend data services.

- Strong analytical, debugging, and problem-solving skills.

- Experience working in production-scale environments handling large datasets.

Good to Have :

- Experience with Databricks, Airflow, dbt, or Snowflake.

- Exposure to real-time streaming pipelines and event-driven architectures.

- Familiarity with Docker, Kubernetes, and CI/CD pipelines.

- Experience supporting analytics, ML, or AI-driven data platforms.

- Exposure to modern engineering workflows and AI-assisted development tools.

Qualifications :

- Bachelors degree in Computer Science, Engineering, or a related field.

- Equivalent practical experience will also be considered.