Key skills
SnowflakeSQLData TransformationData ModelingETL/ELT PipelinesSQL ServerPythonCDC-based ingestion toolsBI ToolsGitOrchestration toolsAWS ServicesSnowflake certificationsETLELTData WarehousingAnalyticsBITableauPower BIAirflowdbtFivetranAWSLambdaS3GlueVersion ControlCI/CD
About this role
CES is a company with over 26 years of experience in Software Product Development and Digital Transformation Consulting Services. They are seeking a Data Engineer to design, develop, and maintain scalable data pipelines for an enterprise HCM data platform, focusing on data quality and governance for K-12 education clients.
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
Requirements:
- 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
- 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)