ERP Data Engineer II: Real-Time Pipelines & Cloud

Fisher Dynamics

Saint Clair Shores (MI)

On-site

USD 95,000 - 135,000

Full time

10 days ago

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Benefits offered by this job

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

Job summary

Fisher Dynamics seeks a Data Engineer II to architect and build scalable data pipelines and cloud data infrastructure powering its ERP platform and embedded AI capabilities. This onsite role in Saint Clair Shores, MI collaborates with ML/AI, software engineering, and business stakeholders to enable real-time analytics, data governance, and reliable data migrations from Plex.

You will design and implement ETL/ELT processes, create real-time streaming pipelines, and optimize cloud data

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 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.

Responsibilities

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.