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. What you’ll be doing 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. Required qualifications 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 BigQuery , 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. Preferred qualifications 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. Benefits 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 Work environment and location 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 . Technologies Python, Scala, Java, SQL, Airflow, Prefect, Dagster, AWS (Redshift, S3), Google BigQuery, Azure (including Azure Data Lake), Spark, Hadoop, Kafka, Flink, Docker, Git #J-18808-Ljbffr