Key Responsibilities

Data Integration & Architecture

    ● Design and implement scalable enterprise data integration architecture across ERP, EPM, QMS, CPT, Quote Management, and other enterprise applications.

    ● Develop robust ETL/ELT pipelines for high-volume, multi-source data ingestion and transformation.

    ● Build reusable data transformation frameworks to standardize and normalize data across multiple business units.

    ● Establish master data management (MDM) processes for product hierarchies, SKU mappings, and cross-system reconciliation.

    ● Develop automated data quality validation, monitoring, and exception handling frameworks.

    ● Implement metadata management, data lineage, and governance standards to ensure traceability and compliance.

API Development & Enterprise Integration

    ● Design, develop, and maintain high-performance RESTful APIs and GraphQL services for enterprise applications and AI model consumption.

    ● Build secure API layers enabling seamless communication between forecasting models and business applications.

    ● Develop middleware and integration services connecting Finance, Operations, Supply Chain, Sales, and AI platforms.

    ● Implement API gateways, authentication, authorization, monitoring, and lifecycle management.

    ● Optimize API performance to support high-volume, low-latency enterprise workloads.

    ● Produce comprehensive API documentation and developer enablement materials.

Real-Time Data Processing

    ● Build and optimize streaming data pipelines for near real-time ingestion and processing.

    ● Develop infrastructure supporting anomaly detection for pricing, forecasting deviations, derates, and operational exceptions.

    ● Create automated alerting mechanisms and recommendation engines for proactive business decision-making.

    ● Enable both scheduled and on-demand data refreshes while maintaining sub-24-hour processing cycles.

    ● Support real-time dashboards and analytics for planning and forecasting.

System Integration & Data Governance

    ● Develop enterprise connectors using modern integration patterns for ERP, EPM, QMS, CPT, CRM, and other business systems.

    ● Implement reconciliation processes and validation checkpoints to ensure data consistency across platforms.

    ● Establish data governance policies, security controls, role-based access, and audit capabilities.

    ● Integrate operational and financial datasets to support forecasting, profitability, margin, and planning analytics.

    ● Maintain version control and audit trails for data pipelines, business rules, and forecasting assumptions.

Performance, Monitoring & Optimization

    ● Monitor integration pipelines, API performance, and overall platform health.

    ● Continuously optimize data pipelines for scalability, reliability, and cost efficiency.

    ● Troubleshoot production issues and perform root cause analysis.

    ● Document technical architecture, integration patterns, APIs, and data models.

    ● Collaborate with analytics, AI/ML, platform engineering, and business teams to improve platform performance.

Required Qualifications

Education

    ● Bachelor's degree in Computer Science, Information Technology, Engineering, or a related discipline.

● Master's degree is preferred.

Experience

    ● 7+ years of experience in Integration Development, Data Engineering, or Enterprise Integration.

    ● 4+ years designing and implementing enterprise ETL/ELT platforms.

    ● Hands-on experience integrating ERP, EPM, Manufacturing, or Supply Chain systems.

    ● Proven experience building scalable, production-grade integration platforms supporting high-volume enterprise data.

    ● Experience with enterprise API development and microservices architecture.

    ● Demonstrated success delivering highly available production systems with 99%+ uptime.

Technical Skills

Data Integration & ETL

    ● Apache Airflow

    ● Talend

    ● Informatica

    ● dbt

    ● Custom ETL frameworks

    ● SQL

    ● Python

    ● Java

    ● Scala

Data Platforms

    ● Snowflake

    ● Amazon Redshift

    ● Google BigQuery

    ● Azure Synapse Analytics

    ● Data quality and validation frameworks

    Streaming & Real-Time Processing

    ● Apache Kafka

    ● Spark Streaming

    ● AWS Kinesis

    ● Event-driven architecture

    ● Real-time data processing frameworks

API & Application Development

    ● RESTful APIs

    ● GraphQL (preferred)

    ● FastAPI

    ● Flask

    ● Spring Boot (preferred)

    ● API Gateway implementation

    ● Microservices architecture

    ● OAuth2, JWT, API Security

Cloud & DevOps

    ● AWS, Azure, or Google Cloud Platform

    ● Docker

    ● Kubernetes

    ● CI/CD pipelines

    ● Infrastructure as Code

    ● Git

    ● DevOps best practices

Databases

    ● PostgreSQL

    ● MongoDB

    ● Spark ecosystem

    ● Hadoop ecosystem

    ● Vector Databases (Pinecone, FAISS, Weaviate, Milvus)

Domain Knowledge

    ● Supply Chain and Manufacturing systems

    ● Financial Planning & Analysis (FP&A)

    ● Forecasting and Demand Planning

    ● Pricing and Quote-to-Cash processes

    ● Enterprise Data Governance

    ● Master Data Management

    ● Cross-functional enterprise integrations

Soft Skills

    ● Strong analytical and problem-solving capabilities.

    ● Excellent communication and stakeholder management skills.

    ● Ability to explain complex technical concepts to business users.

    ● Strong ownership with a proactive and solution-oriented mindset.

    ● Ability to manage multiple priorities in a fast-paced environment.

    ● Collaborative team player with strong documentation skills.

Preferred Qualifications

    ● Experience building AI/ML data pipelines and feature engineering workflows.

    ● Exposure to enterprise forecasting platforms and financial planning solutions.

    ● Experience implementing real-time anomaly detection systems.

    ● Knowledge of financial close and accounting processes.

    ● Cloud certifications (AWS, Azure, or GCP).

    ● Experience contributing to open-source data engineering projects.

    ● Familiarity with IATF 16949 or Quality Management Systems.

Nice to Have

    ● Experience working in manufacturing, automotive, semiconductor, or industrial domains.

    ● Exposure to AI-driven forecasting and predictive analytics platforms.

    ● Knowledge of enterprise integration platforms such as MuleSoft, Boomi, or Azure Integration

Services.

    ● Experience with event-driven architecture and serverless integrations.

    ● Understanding of DataOps and MLOps best practices