Job Title: Data Engineer Location: Arden Hills, MN (Hybrid – 3 days a week), Need only Locals to MN or nearby states like (Michigan, Wisconsin, Iowa, North Dokota, South Dokota)
Priyanka S
Job Title: Data Engineer Location: Arden Hills, MN (Hybrid – 3 days a week) Duration: 12+ Months Rate: $50/hr
Need only Locals to MN or nearby states like (Michigan, Wisconsin, Iowa, North Dokota, South Dokota)
Job Summary: The Data Engineer will build reliable, scalable data solutions that strengthen trusted HR and enterprise analytics. This role works closely with business analysts, lead data engineers, and the HR team on site to deliver well‑managed data pipelines, improve data quality, and enhance data‑driven operations across the organization.
Required Competencies/Skills:
Core Experience: 7+ years in SQL, data engineering, and data modeling
Data Platforms: Builds and supports data warehouses, data lakes, and lake house environments
Snowflake: Minimum 2 years of hands‑on experience
Delivery Leadership: Leads full‑lifecycle data engineering or reporting initiatives
Data Ingestion: Designs and builds ingestion patterns for files, APIs, databases, CDC, replication, and streaming/message‑based data sources
Data Pipelines: Builds, optimizes, and operates reliable ETL/ELT pipelines and integrated datasets
DevOps: Uses CI/CD, automated testing, and deployment practices for data solutions
Scripting: Uses scripting languages, preferably Python, for automation
Ownership: Works independently, manages priorities, and drives outcomes with minimal supervision
Problem Solving: Strong analytical, troubleshooting, and root cause analysis skills
Communication: Clear coordination with technical and business partners
Data Security: Applies encryption, anonymization, masking, and access‑aware design
Modern Data Architecture: Understands warehouse, lake, lake house, and cloud‑based designs
Azure Familiarity: Knowledge of Azure services for storage, integration, processing, orchestration, and security
Orchestration: Manages scheduling, monitoring, and data flow reliability
Metadata Management: Improves usability, lineage, and governance
Version Control: Supports quality, traceability, and collaboration
Scalability: Designs pipelines with performance and distributed processing considerations
Preferred Competencies/Skills:
Advanced Platform Optimization: Optimizes Snowflake and Databricks/Spark workloads (streams, tasks, dynamic tables, performance tuning)
HR Data Experience: Works with HR systems like Workday, supports workforce analytics and employee lifecycle reporting
HR Data Governance: Applies privacy, minimization, masking, and access practices for confidential employee data
