Data Engineer with Advanced SQL

We are seeking a skilled Data Engineer with expertise in Python, Snowflake and Databricks to join our dynamic team. The ideal candidate will be responsible for designing, building, and maintaining efficient, scalable, and reliable data pipelines and solutions. This role requires a deep understanding of data engineering principles, proficiency in modern data platforms and the ability to collaborate effectively with cross-functional teams to drive data-driven decisions.

Mandatory Requirements:
Education: Bachelors degree in Computer Science, Engineering, Information Systems, or a related field.

Experience:
Minimum 3 years of experience in data engineering.
Proven experience with Python for data manipulation and automation.
Strong expertise in Snowflake for data warehousing solutions.
Proficient in using Databricks for data processing and analytics.

Technical Skills:
Solid understanding of SQL and relational databases.
Experience with ETL/ELT processes and tools.
Familiarity with cloud platforms (e.g., AWS, Azure, GCP).
Knowledge of data modelling, data architecture, and data integration.
Experience with version control systems such as Git.

Soft Skills:
Strong analytical and problem-solving abilities.
Excellent communication and collaboration skills.
Ability to work in a fast-paced, agile environment.

Nice to Have:
Experience with additional programming languages (e.g., Scala, Java).
Familiarity with other data warehousing solutions (e.g., Redshift, BigQuery).
Knowledge of machine learning frameworks and tools.
Experience with real-time data processing technologies (e.g., Kafka, Spark Streaming).
Understanding of data governance and data security best practices.
Certifications related to data engineering or cloud platforms.

Responsibilities:
Design, develop, and maintain data pipelines to support business intelligence, analytics, and machine learning initiatives.
Implement data integration solutions using Python, Snowflake, and Databricks.
Optimize data workflows for performance, scalability, and reliability.
Collaborate with data scientists, analysts, and other stakeholders to understand data needs and deliver high-quality data solutions.
Ensure data quality and integrity by implementing robust data validation and monitoring processes.
Develop and maintain comprehensive documentation for data engineering processes and solutions.
Stay up-to-date with emerging trends and technologies in data engineering and recommend improvements to current processes and architectures.
Participate in code reviews, providing constructive feedback to peers to maintain high coding standards and best practices.
Support and troubleshoot data-related issues, ensuring timely resolution and minimal disruption to business operations.