[Remote] Senior Data Engineer

Note: The job is a remote job and is open to candidates in USA. AIPPY Technologies is seeking a Senior Data Engineer to serve as a strategic consultant supporting a client’s enterprise data modernization and AI initiatives. The role designs, builds, optimizes, and maintains data pipelines and models that integrate enterprise systems into cloud data platforms, enabling reporting, analytics, and AI use cases.

Responsibilities

• Implement modern data warehouse architecture patterns, including lakehouse and medallion architectures (raw, curated, consumption) that are scalable, performant, and maintainable
• Integrate data from multiple systems, including D365 F&O/CE, SAP, Infor XA, and other ERP systems into unified data models that support enterprise reporting, analytics, and AI
• Design, build, and optimize scalable data pipelines that support batch, near-real-time, and real-time data integration patterns
• Measure and monitor performance and cost of data pipelines, ensuring solutions meet SLAs for data availability, quality, refresh performance, and efficiency
• Assemble, transform, and manage large, complex datasets, ensuring consistency, reliability, and usability across business domains
• Ensure data quality is embedded in pipelines by implementing validation, monitoring, alerting, and error-handling mechanisms to support trusted downstream consumption
• Build and maintain data integration frameworks using Azure services such as Synapse Analytics, Fabric, and Databricks, along with SQL, Python, and Spark-based processing
• Identify and implement process improvements to increase scalability, automate manual processes, and optimize data delivery
• Develop analytical datasets that enable actionable insights into business performance, operational efficiency, and customer metrics
• Collaborate with Data Architects, data & AI engineers, analytics teams, and business stakeholders to ensure solutions align with business requirements and architectural standards
• Create and maintain technical documentation, including data mappings, pipeline designs, and operational runbooks
• Contribute to testing, QA, and validation of data pipelines and systems to ensure reliability and accuracy
• Support building an AI-ready data foundation by:
• Delivering clean, structured, and well-documented datasets
• Enabling efficient data access patterns for advanced analytics
• Supporting downstream use cases such as exploratory analysis and model consumption
• Ensuring compliance with security, privacy, and enterprise standards in all data solutions
• Participate in Agile/Scrum processes to enable iterative, collaborative delivery

Skills

• Strong understanding of data engineering best practices and modern cloud data platforms
• Expertise in data modeling, including relational, dimensional, and lakehouse-based approaches
• Ability to translate business requirements into technical data solutions
• Strong collaboration and communication skills across technical and business teams
• Ability to manage multiple concurrent priorities in a fast-paced environment
• Experience debugging and resolving complex data pipeline and performance issues
• Strong problem-solving mindset with ownership and accountability
• Bachelor's degree in Computer Science, Information Systems, Engineering, or equivalent experience
• 5–8+ years of experience in data engineering or analytics development in a cloud environment
• Strong experience with ETL/ELT pipeline development and data integration using data integration tools like Databricks Notebook, Talend, Informatica, or Boomi
• Hands-on experience with Azure-based data platforms, including: • Azure Databricks • Azure Data Factory (ADF) • Azure Synapse Analytics • Microsoft Fabric • Azure Data Lake Storage (ADLS) • Azure Synapse Link / Fabric Link • Azure SQL Database • Azure DevOps (CI/CD pipelines)
• Advanced proficiency in SQL and experience with Python (or similar languages)
• Experience working with Spark, Pandas, or distributed data processing frameworks
• Experience working in Agile and DevOps environments, including CI/CD practices and source control
• Experience building data solutions that support modern analytics and AI-ready data ecosystems
• Full-time, W2 only, No sponsorship
• H-1 B transfer is okay for the right candidate; no new H-1 B sponsorship
• Manufacturing industry experience in complex data environments
• Experience with Microsoft Dynamics 365 F&O and D365 CE data integration and analytics
• Experience supporting advanced analytics or AI/ML workloads through well-engineered data pipelines
• Understanding of patterns that enable AI-ready platforms, including master data management, data governance frameworks, and trusted data products that support analytics, machine learning, and generative AI use cases
• Experience integrating ERP and CRM systems into enterprise analytics platforms

Company Overview