[Hiring] Data Engineer @CESIT

Role Description

Design, develop, and maintain scalable data pipelines for an enterprise HCM data platform serving K-12 education clients. You will build end-to-end data solutions using modern cloud technologies, implement medallion architecture (Bronze/Silver/Gold), and ensure data quality and governance across the platform.

Key Responsibilities

• Design and implement data ingestion pipelines using CDC/CT (Change Tracking) from SQL Server sources
• Build and maintain medallion architecture (Bronze → Silver → Gold) data layers in Snowflake
• Develop data transformation models using tools like dbt, AWS Glue, or Snowflake native features (stored procedures, tasks)
• Implement SCD Type 1 and Type 2 patterns for historical data tracking
• Design and implement Row-Level Security (RLS) for multi-tenant data access
• Create and optimize Snowflake objects including tables, views, streams, tasks, and stored procedures
• Design data models supporting complex reporting requirements for absence management, workforce analytics, and substitute tracking
• Ensure Gold layer is optimized for BI tool consumption (Power BI, Tableau, or other reporting tools)
• Establish data quality checks, monitoring, and alerting mechanisms
• Document technical designs, data dictionaries, and lineage documentation
• Mentor junior team members and conduct code reviews

Qualifications

• Snowflake: 2+ years hands-on experience with data warehousing, performance tuning, secure views, streams/tasks
• SQL: Advanced SQL skills including complex joins, window functions, CTEs, and query optimization
• Data Transformation: Experience with any transformation framework (dbt, AWS Glue, Snowflake stored procedures, or similar)
• Data Modeling: Strong experience with dimensional modeling, star/snowflake schemas, and SCD implementations
• ETL/ELT Pipelines: Experience with data pipeline design patterns, CT, and incremental loading strategies
• SQL Server: Experience with SQL Server as source system including CDC and Change Tracking
• Python: Proficiency in Python for data processing and automation scripts

Nice to Have

• CDC-based ingestion tools (Snowflake OpenFlow, Fivetran, Airbyte, AWS DMS)
• SPCS (Snowpark Container Services) for containerized workloads
• BI Tools: Understanding of how BI tools (Power BI, Tableau, QuickSight) consume data via DirectQuery/Live Connection
• Git: Version control and CI/CD pipelines for data projects
• Orchestration tools (Airflow, Dagster, AWS Step Functions) for pipeline scheduling
• AWS Services: S3, Glue, Lambda, PrivateLink, VPC connectivity
• Snowflake certifications (SnowPro Core, SnowPro Advanced Data Engineer)