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Job Description
Job Overview:
- We are seeking an experienced Python SQL and ETL Developer to create, develop, and sustain scalable data pipelines and integration solutions.
- The successful applicant will collaborate closely with data engineers, analysts, and business stakeholders to guarantee reliable, high-quality data delivery for reporting, analytics, and downstream applications.
Primary Duties:
- Design, develop, and maintain Python applications.
- Create clean, efficient, and reusable Python code.
- Develop automation scripts and data processing solutions.
- Engage with databases using SQL.
- Conduct code reviews and mentor junior developers.
- Investigate and resolve application and data-related issues.
- Assist with production deployments and system enhancements.
- Develop, maintain, and optimize ETL pipelines to extract, transform, and load data from various sources.
- Write scalable, efficient, and well-documented Python scripts for data processing and automation purposes.
- Design and refine complex SQL queries, views, and stored procedures for optimal performance and accuracy.
- Carry out data validation, quality assessments, and reconciliation to ensure data integrity.
- Diagnose and address data pipeline failures and performance challenges.
- Collaborate with data analysts, data scientists, and business teams to gather and understand data requirements.
- Implement best practices for data security, governance, and compliance.
- Maintain technical documentation for ETL workflows and data models.
Technical Qualifications:
- Extensive experience in Python development.
- Strong understanding of SQL and data management.
- Experience in production environments.
- Proficient in Python for data manipulation, scripting, and automation.
- Advanced knowledge of SQL joins, subqueries, window functions, and performance tuning.
- Hands-on experience with ETL and ELT tools or frameworks.
- Experience with relational databases such as e.g., MySQL, PostgreSQL, SQL Server, Oracle.
- Strong grasp of data warehousing principles, including fact and dimension tables, and star schema.
- Able to work with large datasets and enhance data processing workflows.
- Excellent analytical, problem-solving, and debugging abilities.
Additional Qualifications:
- Familiarity with cloud platforms like AWS, Azure, or GCP.
- Experience with big data technologies, including Spark and Hadoop.
- Exposure to workflow schedulers such as Airflow, Prefect, or Cron.
- Knowledge of CI/CD pipelines and version control using Git.
- Understanding of data governance and lineage tools.