Fisher Dynamics is looking for a Data Engineer II to help power its ERP platform and embedded AI and LLM capabilities. In this onsite role in Saint Clair Shores, MI, you will design and deliver scalable, reliable data pipelines and cloud data infrastructure, supporting real-time streaming and feature pipelines, data governance, and data migration and integrations. You will partner closely with ML/AI engineers, software engineering, and business stakeholders to ensure trusted data foundations for operational and analytical use.
Responsibilities
- Design and build scalable, fault-tolerant data pipelines for ERP data ingestion, transformation, and loading.
- Implement ETL/ELT workflows to migrate legacy ERP data into the new ERP system, including data validation and quality checks.
- Build real-time streaming pipelines using Kafka, Spark, or similar technologies for continuous data flow.
- Develop batch processing jobs for scheduled transformations and aggregations.
- Ensure pipelines support large volumes, complex transformations, and operational resilience.
- Establish data governance policies, standards, and procedures for ERP data.
- Create monitoring and validation frameworks for data accuracy and consistency, including data profiling, cleansing, and quality tooling.
- Document data lineage, metadata, and data dictionaries to support transparency and compliance.
- Monitor data quality metrics and SLAs, alert on issues, and drive resolution.
- Design and implement cloud-based data architecture on AWS, GCP, or Azure (data warehouses, data lakes, and related components).
- Build and optimize storage solutions for ERP transactional and analytical data.
- Implement data security controls, including encryption and access controls for sensitive financial and operational data.
- Optimize infrastructure for performance, cost, and scalability, and troubleshoot pipeline and platform issues.
- Collaborate with ML/AI engineers on feature requirements and data needs, including feature stores and feature pipelines for model training and inference.
- Engineer ML-ready features from raw ERP inputs (transactions, master data, time-series), and support real-time feature serving for low-latency inference.
- Support exploratory data analysis and data debugging for ML/AI initiatives.
- Lead data migration from Plex to the new ERP system with validation and reconciliation.
- Build integrations with external sources (suppliers, customers, market data), including synchronization and consistency checks.
- Manage historical data and archive strategies, support data cutover activities, and perform validation.
- Conduct load testing and capacity planning for data infrastructure.
Requirements
- Bachelor’s degree in Computer Science, Data Science, Engineering, or a related field.
- 4-6 years of professional data engineering experience building production data systems.
- Master’s degree preferred.
- Demonstrated experience designing and implementing large-scale ETL/ELT pipelines and required data architectures.
- ERP system data integration or data warehousing experience strongly preferred.
- Advanced proficiency in Python, Scala, Java, or similar data engineering languages.
- Expert-level SQL and relational/dimensional database design.
- Strong experience with orchestration tools such as Airflow, Prefect, Dagster.
- Expertise with cloud data platforms including AWS Redshift/S3, Google BigQuery, Azure Data Lake.
- Experience with big data technologies such as Spark, Hadoop, Kafka, Flink.
- Knowledge of data warehousing, data lakes, and data architecture patterns, including data quality practices.
- 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.
- Feature store and ML data pipeline experience is preferred, along with familiarity with ERP systems and business data models.
- Strong problem-solving, debugging, and collaboration skills, including clear communication with data scientists and engineers.
Benefits
- 401(k) and 401(k) matching
- Dental insurance, Vision insurance, Health insurance, and Life insurance
- Health savings account and Flexible spending account
- Employee assistance program
- Employee discount
- Flexible schedule
- Paid time off
- Professional development assistance and tuition reimbursement
Work Environment
This position is in-person. The working environment and physical requirements are typical of an office setting and manufacturing environment. The role requires collaboration with technical teams and business stakeholders.
Physical Demands
Ability to lift 40 lbs.
Technologies
Python, Scala, Java, SQL, Airflow, Prefect, Dagster, AWS, AWS Redshift, S3, Google BigQuery, Azure, Azure Data Lake, Spark, Hadoop, Kafka, Flink, Docker, Git
