Fisher Dynamics is building modern data capabilities to support an ERP platform and its embedded AI and LLM features. As a Data Engineer II in Saint Clair Shores, MI, you’ll architect and deliver scalable data pipelines and cloud data infrastructure that enable real-time streaming, batch processing, and data governance. You’ll also help power data migration from Plex and integrations with external sources, collaborating closely with ML/AI, software engineering, and business stakeholders.
What you’ll do
- Design and build scalable, fault-tolerant data pipelines for ERP data ingestion, transformation, and loading.
- Develop ETL/ELT workflows to migrate legacy ERP data into the new ERP system with data validation and quality checks.
- Create real-time streaming pipelines using Kafka, Spark, or similar technologies for continuous data flow.
- Build batch processing jobs for scheduled transformations and aggregations.
- Establish data governance policies, standards, and procedures for ERP data.
- Implement data quality monitoring and validation to maintain accuracy and consistency.
- Build data profiling, cleansing, and validation tooling to support high-quality datasets.
- Document data lineage, metadata, and data dictionaries for transparency and compliance.
- Monitor pipeline 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 services).
- Build and optimize data storage for ERP transactional and analytical workloads.
- Implement data security including encryption and access controls for sensitive financial and operational data.
- Optimize performance, cost, and scalability of data infrastructure; monitor and troubleshoot data infrastructure issues.
- Collaborate with ML/AI engineers to align on feature requirements and data needs for model training and inference.
- Design and build feature stores and feature pipelines, engineer ML-optimized features from raw ERP data (transactions, master data, time-series), and support low-latency real-time feature serving.
- Support ML/AI efforts with exploratory data analysis and data debugging.
- Lead data migration from Plex with validation and reconciliation.
- Build integrations with external data sources (suppliers, customers, market data), and implement synchronization and consistency checks between source and target systems.
- Manage historical data and archive strategies, support data cutover activities and validation, and monitor/optimize pipeline performance and query efficiency.
- Set up monitoring and alerting for pipeline health and perform load testing and capacity planning.
What you bring
- Bachelor’s degree in Computer Science, Data Science, Engineering, or related field.
- Master’s degree preferred.
- 4-6 years of professional data engineering experience building production data systems.
- Proven experience designing and implementing large-scale ETL/ELT pipelines and required data architectures.
- Experience with ERP system data integration or data warehousing strongly preferred.
- Advanced proficiency in Python, Scala, Java, or similar data engineering languages.
- Expert-level SQL and relational/dimensional database design.
- Experience with orchestration tools such as Airflow, Prefect, or Dagster.
- Expertise in cloud data platforms: AWS Redshift/S3, Google BigQuery, and/or Azure Data Lake.
- Experience with big data technologies including Spark, Hadoop, Kafka, and Flink.
- Strong understanding of data warehousing, data lakes, ETL/ELT patterns, 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.
- Feature stores and ML data pipelines preferred; familiarity with ERP systems and business data models preferred.
- Strong problem-solving and debugging skills, with excellent communication and collaboration with data scientists and engineers.
Tools and technologies you’ll work with
Python, Scala, Java, SQL, Airflow, Prefect, Dagster, AWS, AWS Redshift, S3, Google BigQuery, Azure, Azure Data Lake, Spark, Hadoop, Kafka, Flink, Docker, Git
Benefits
- 401(k) and 401(k) matching
- Health insurance, Health savings account, Life insurance, Vision insurance
- Dental insurance
- Flexible schedule
- Flexible spending account
- Paid time off
- Employee assistance program
- Employee discount
- Professional development assistance
- Tuition reimbursement
Work environment
This position is in person. The working environment and physical requirements are typical of an office setting and manufacturing environment, with collaboration across technical teams and business stakeholders.
Physical demands
Ability to lift 40 lbs.
