Job Summary
The Mid-Level Data Analyst / Engineer will develop and maintain data processing solutions and pipelines using Python, SQL, and, where required, Java. The role involves working with cloud platforms, big data frameworks, relational databases, and data warehouses to build scalable, reliable, and maintainable data solutions. The engineer will support data modeling, query optimization, data quality monitoring, and workflow orchestration while collaborating with cross-functional teams to ensure high-quality deliverables and production stability.
Key Responsibilities
• Develop and maintain data processing solutions and pipelines using Python, SQL, and Java where required.
• Design, implement, and maintain scalable, reliable, and maintainable data pipelines.
• Apply data modeling concepts, including star and snowflake schemas and fact and dimension tables.
• Work with cloud platforms and their data services to support data processing and engineering requirements.
• Develop and optimize data processing workflows using big data frameworks such as Apache Spark, Databricks, or equivalent technologies.
• Work with relational databases and data warehouses to support data integration, storage, and analytical requirements.
• Optimize SQL queries and database performance to improve processing efficiency.
• Use workflow orchestration tools to manage and coordinate data pipeline execution.
• Implement data quality checks, monitoring, and logging to maintain data accuracy and pipeline reliability.
• Perform code reviews and provide technical guidance to junior engineers to support high-quality deliverables.
• Collaborate with cross-functional teams to understand requirements and deliver effective data solutions.
• Take ownership of assigned deliverables, emphasizing first-time-right execution and production stability.
Required Qualifications
• 4-8 years of experience in data analytics, data engineering, or a related field.
• Strong proficiency in Python and/or SQL for data processing and pipeline development.
• Working knowledge of Java for data processing and pipeline development, where required.
• Strong understanding of data modeling concepts, including star and snowflake schemas and fact and dimension tables.
• Hands-on experience with cloud platforms and their data services.
• Experience with big data frameworks such as Apache Spark, Databricks, or equivalent technologies.
• Strong knowledge of relational databases and query optimization.
• Experience working with data warehouses.
• Familiarity with workflow orchestration tools.
• Experience implementing data quality checks, monitoring, and logging.
• Strong analytical thinking and problem-solving skills.
• Very good communication skills and the ability to collaborate with cross-functional teams.
• Ability to perform code reviews and mentor junior engineers.
• Strong ownership mindset with a focus on first-time-right delivery and production stability.
