Senior Data Engineer

JOB RESPONSIBILITIES:

• Design, build, and maintain ETL/ELT pipelines for automated data ingestion, transformation, and validation.

• Establish a centralized data storage system, starting with lightweight solutions and scaling toward cloud-based infrastructure.

• Collaborate with analysts and business teams to translate reporting needs into scalable, reusable data models.

• Implement data quality checks, logging, and monitoring to ensure reliability and transparency of data flows.

• Refactor existing Python/Jupyter workflows into structured, production-ready codebases.

• Evaluate and recommend tools for data warehousing, orchestration, and cloud migration.

• Define and promote best practices in version control, documentation, and reproducibility.

JOB REQUIREMENTS:

• Strong proficiency in Python (pandas, PySpark, or similar libraries for data processing).

• Solid understanding of SQL and experience with relational databases.

• Hands-on experience designing or maintaining ETL pipelines and workflow orchestration tools (e.g., Airflow, Prefect, Luigi).

• Good grasp of data modeling, schema design, and data governance principles.

• Experience handling large datasets and optimizing data performance.

• Comfortable working in environments with minimal existing infrastructure and building systems from scratch.

• Strong analytical thinking, problem-solving skills, and ability to work with both technical and non-technical stakeholders.

NICE TO HAVE:

• Experience with cloud platforms (AWS, GCP, or Azure) and cloud-native data services.

• Knowledge of data warehousing technologies (Snowflake, BigQuery, Redshift, or Databricks).

• Familiarity with CI/CD pipelines, Docker, or containerized workflows.

• Exposure to business intelligence tools (Power BI, Tableau, or similar).