Data Engineer II

Fisher Dynamics is looking for a Data Engineer II to architect and build scalable data pipelines and cloud data infrastructure that power an ERP platform and its embedded AI/LLM capabilities. In this onsite role in Saint Clair Shores, MI
, you will help drive data governance, real-time streaming, and feature pipelines, while supporting ERP data migration from Plex and integrations with external data sources. You will collaborate closely across ML/AI, software engineering, and business stakeholders.

• Design and build scalable, fault-tolerant data pipelines for ERP data ingestion, transformation, and loading.
• Implement ETL/ELT processes that migrate legacy ERP data into the new ERP system, including data validation and quality checks.
• Create real-time streaming pipelines using Kafka
  , Spark
  , or similar technologies to support continuous data flow.
• Develop batch processing jobs for scheduled transformations and aggregations.
• Build and optimize cloud data architecture on AWS
  , GCP
  , or Azure (data warehouses, data lakes, and related components).
• Implement data governance policies, standards, and procedures for ERP data.
• Establish data quality monitoring and validation frameworks, including data profiling, cleansing, and validation tools.
• Document data lineage, metadata, and data dictionaries to support transparency and compliance.
• Monitor data quality metrics and SLAs, alert on data issues, and drive resolution.
• Build data security controls, including encryption and access controls for sensitive financial and operational data.
• Monitor, troubleshoot, and optimize data infrastructure for performance, cost, and scalability.
• Collaborate with ML/AI engineers on feature requirements and data needs, including building feature stores and feature pipelines.
• Engineer features from ERP raw data (transactions, master data, time-series) optimized for ML training and inference.
• Support ML/AI teams with exploratory data analysis and data debugging.
• Lead data migration from Plex to the new ERP system with data validation and reconciliation.
• Build integrations with external data sources such as suppliers, customers, and market data, including synchronization and consistency checks.
• Manage historical data and archive strategies, support data cutover activities, and validate outcomes.
• Conduct load testing and capacity planning for data infrastructure.

• Bachelor’s degree in Computer Science, Data Science, Engineering, or related field.
• 4-6 years of professional data engineering experience building production data systems.
• Demonstrated experience designing and implementing large-scale ETL/ELT pipelines and required data architectures.
• Advanced proficiency in Python
  , Scala
  , Java
  , or similar data engineering languages.
• Expert-level SQL and relational/dimensional database design.
• Strong experience with data pipeline orchestration tools such as Airflow
  , Prefect
  , or Dagster
  .
• Expertise in cloud data platforms including AWS Redshift/S3
  , Google Big Query
  , and Azure Data Lake
  .
• Experience with big data technologies including Spark
  , Hadoop
  , Kafka
  , Flink
  .
• Strong understanding of ETL/ELT patterns, data transformation, and data quality.
• Experience with version control (
  Git
  ) and data pipeline version management.
• Proficiency with containerization (
  Docker
  ) and orchestration platforms.
• Understanding of data governance, security, and compliance requirements.
• Strong problem-solving and debugging skills.
• Excellent communication skills and ability to collaborate with data scientists and engineers.

• Master’s degree.
• Experience with ERP system data integration or data warehousing.
• Experience with feature stores and ML data pipelines.
• Familiarity with ERP systems and business data models.

• 401(k) and 401(k) matching
• Health insurance, Health savings account
• Dental insurance, Vision insurance
• Life insurance
• Employee assistance program
• Flexible schedule
• Flexible spending account
• Paid time off
• Professional development assistance
• Tuition reimbursement
• Employee discount

This is an in-person position in an office and manufacturing environment. The role involves collaboration with technical teams and business stakeholders.

Physical demand: Ability to lift 40lbs
.

Python, Scala, Java, SQL, Airflow, Prefect, Dagster, AWS (Redshift, S3), Google Big Query, Azure (including Azure Data Lake), Spark, Hadoop, Kafka, Flink, Docker, Git