Programmer Analyst – Data Solutions

Mandatory Skills & Requirements

• 6+ years of experience in Data Engineering, Software Development, Business Intelligence, or Data Solutions.
• Strong SQL development skills and experience working with large-scale analytical datasets.
• Hands-on experience with Python, Spark/PySpark, and Snowflake.
• Strong understanding of relational databases, MPP databases, distributed data warehouses, and cloud data platforms.
• Working knowledge of Delta Lake, Apache Iceberg, partitioning strategies, file formats, storage optimization, and query performance tuning.
• Experience with data integration, transformation, pipeline development, and distributed data processing.
• Understanding of cloud-native analytics platforms and modern data warehouse/lakehouse architectures.
• Strong analytical, troubleshooting, and problem-solving skills.
• Ability to work independently, manage priorities, and collaborate effectively with technical teams.

Key Responsibilities

• Analyze business and technical requirements to develop scalable data and analytics solutions.
• Design, develop, test, deploy, and maintain data pipelines using SQL, Python, Spark, Snowflake, Microsoft Fabric, and related technologies.
• Support new development, application maintenance, enhancements, and defect resolution.
• Develop and optimize SQL queries, data transformations, and reusable data assets.
• Contribute to data modeling, data mapping, metadata management, and data lineage documentation.
• Implement lakehouse solutions and optimize data storage, processing, and query performance.
• Investigate data quality issues, perform root cause analysis, and ensure data integrity.
• Collaborate with senior engineers and architects to deliver secure, reliable, and maintainable solutions.
• Participate in code reviews, testing, deployments, technical documentation, and continuous improvement.
• Provide production support for cloud-based and distributed data platforms.

Preferred Skills

• Microsoft Fabric: OneLake, Lakehouse, Data Factory, Notebooks, Semantic Models, and Power BI.
• Snowflake data platform experience.
• AWS data and analytics services.
• Data governance, data quality, and metadata management.
• Financial, accounting, or enterprise reporting data experience.
• Financial Services industry experience.
• Agile delivery methodologies and Git-based development workflows.