• Design, build, and maintain scalable ETL/ELT data pipelines • Integrate data from internal and external systems using REST APIs • Develop and maintain Python scripts for data processing and automation • Work with CLI tools for deployments, monitoring, and troubleshooting • Leverage cloud services on AWS and/or GCP for data workflows • Identify and resolve data quality, pipeline, and integration issues • Create and maintain technical documentation and process guidelines

This description is a summary of our understanding of the job description. Click on 'Apply' button to find out more. Role Description If you are someone who can lead and inspire teams while being hands-on with modern data technologies, apply to this position! Manager Data Engineering will work closely with Shure associates located in North America, Europe, and Asia to build, enhance, and maintain data and analytics solutions to meet the global business needs. Responsible for engineering and supporting data pipelines leveraging Shure technology investments in AWS, Informatica, Snowflake. Data will include structured and unstructured, internal, and external, Internet of Things, etc. This role requires exposure to industry best practices, technological trends, the willingness to learn new emerging technologies, and collaboration with the global team. - Manage, mentor, and coach a team of Data Engineers & Data Application Administrators, fostering technical growth and collaboration. - Leverage expertise on data engineering development and support for the connection and ingestion of data source systems into Shure’s data lake and Enterprise Data Warehouse system. - Develop data transformations and load data from multiple sources into Shure’s data lake and/or data warehousing layer. - Work on problems of diverse scopes where analysis of data requires evaluation of identifiable factors. - Mentor new associates and lead the team in adopting best practices. - Proficiency and hands-on experience with AWS Data Engineering Stack, Snowflake, Informatica IDMC. - Drive CI/CD development and code migration using industry best practices. - Lead Scrum teams under SAFe Agile framework with a strong One Team mindset and accountability culture. - Monitor cloud resource utilization and implement cost optimization strategies. - Knowledge & experience of AI/ML models and Generative AI techniques for predictive analytics and AI use cases. - Demonstrate good judgment in selecting methods and techniques for obtaining solutions. - Work on automation, monitoring, and continuous improvement for DataOps operations. - Support for Shure’s data governance initiatives. - Network with senior internal and external personnel in own area of expertise. - Ability to quickly learn emerging technologies and industry trends and proactively drive improvements and innovation. - Develop and implement methods and techniques to improve data extract efficiency, quality, and reliability. - Strongly participate in the requirement gathering process with some guidance from Data Engineers for complex integrations. - Work with Data Architects, IT Systems Analysts, and Business Data Analysts to design and build flexible, scalable, sustainable data models and analytic solutions that meet business needs. - Convert business requirements into technical solutions leveraging Shure’s data application investments. - Document technical solution proposals and final designs. - Provide high-quality code deliverables that meet the standards, perform technical validation, support functional and user acceptance testing. - Work on continuous process and system improvements to ensure reliability of the data platform. - Work on automation of regular processes and build a mechanism of monitoring the work process, flows, and services as defined from time to time. - Provide routine support to business users and functional teams by resolving user Service Desk tickets and Requests in accordance with agreed upon SLAs. - Document and execute unit test cases and perform unit and regression testing. - Adhere and contribute to general IT processes, procedures, and policies. - Other duties as assigned. Qualifications - Bachelor’s degree in engineering (preferably Computer Science) or a master’s degree in computer science. - Minimum of 5+ years of experience managing a team and working with enterprise data warehouse platforms, building and managing data lakes, and using big data technologies. - Minimum of 10+ years’ experience with Data Engineering Solutions. - Minimum of 8+ years’ experience with AWS, Snowflake, Informatica IDMC, or similar. - Ability to convert business function analytical requirements into technical documents and help to develop, validate, and deploy to usage. - Strong knowledge of various data architecture frameworks, domain knowledge, and expertise in designing scalable, efficient data models. - Proficient in AWS technology platform. Experience with solutioning on AWS infrastructure using services like S3, Lambda, Glue, EMR, Redshift, Athena, Kinesis, Step Functions, Glue ETL, Glue Crawler, Data Catalog, Lake Formation, Amazon Aurora, RDS, DynamoDB, Athena. - Proficient in Snowflake DWH Solution and Informatica IDMC or similar integration platforms. - Comprehensive understanding of enterprise business processes, with a strong focus on sales, manufacturing, inventory management, finance, and costing. - Prior experience in working with structured data in an ERP and data warehouse package such as SAP-S/4, Salesforce, or SAP-BW. - Knowledge and fair understanding of structured and non-structured data, Web, IoT, ERP. - Experience of working with integrating and migrating SAP landscape to the AWS using Informatica or other open data integration tools. - Fair understanding of the network and able to troubleshoot and identify issues in application integration. - Knowledge on integration protocols like OData, ODP, Custom API, JDBC, ODBC, File, REST API, and others. - Knowledge of data visualization tools like Tableau/Power BI. - Strong expertise in multi-parallel processing frameworks and applications. - Knowledge of Streaming & Generative-AI Applications. - Strong coding skills in SQL, Python, PySpark, or similar technologies. - Fair understanding of SLA and working on ticketing tools like Service Now. - Demonstrated understanding of business processes and how they affect reporting design and solutions. - Demonstrates good judgment in selecting methods and techniques for obtaining solutions for difficult assignments and of diverse scope. - Able to work on problems of diverse scope where analysis of data or situations requires evaluation of identifiable factors. - Excellent written and verbal communication skills, as well as strong time management skills. - Good problem-solving and root cause analysis skills. - Should have a fair knowledge and working experience on different project management methodologies like SAFe Agile methods. - Possession of any recognized certification (e.g., AWS, Azure, GCP, Snowflake, PMP) is preferred. Benefits - Flexible work arrangements. - Opportunity for all. Company Description Shure’s mission is to be the most trusted audio brand worldwide – and for over a century, our Core Values have aligned us to be just that. Founded in 1925, we are a leading global manufacturer of audio equipment known for quality, reliability, and durability. We engineer microphones, headphones, wireless audio systems, conferencing systems, and more. And quality doesn’t stop at our products. Our talented teams strive for perfection and innovate every chance they get. - Shure is headquartered in the United States. - We have more than 35 regional sales offices, engineering hubs, distribution centers, and manufacturing facilities throughout the Americas, EMEA, and Asia.

Senior Data Engineer – Data and Analytics (Remote) Fusion Education Group is seeking a curious and tenaciously driven individual to lead data and analytics architecture for a data-aware organization. This opportunity will report to the Manager of Data and Analytics and provide mentorship to a small team of Data Engineers and Visualization Developers. This opening requires excellent planning, coordination, and communication skills. As a Senior Data Engineer at Fusion Education Group you will oversee the design, development, and implementation of data and analytics for the company’s data ecosystem. You will be responsible for the entire development lifecycle, appreciating and translating the needs of the user and ensuring the final product meets their expectations while upholding department and company standards. As a Senior Data Engineer, you will architect, build, and optimize the data infrastructure that powers advanced analytics, machine learning, and business intelligence across the organization. You’ll leverage the latest Azure Data Lake architecture, AI services, and cloud-native tools, collaborating with AI Engineers, Data Engineers, Data Analysts, and business stakeholders to deliver reliable, scalable, and secure data solutions. Responsibilities include but are not limited to: - Design, architect and operate modern data platforms on Azure - Architect and maintain data lakes/lakehouses with Azure Data Lake Storage (ADLS) and Databricks. - Establish robust ELT patterns using Azure Data Factory (ADF) pipelines with a focus on cost, performance, and reliability. - Lead the full lifecycle—from prototyping to production deployment, including pipelines, APIs, front/back-end integration, monitoring, and maintenance. - Design scalable, reliable systems; optimize performance, latency, cost, and integrate telemetry for iterative improvement - Build intelligent data products using Azure AI - Productionize ML workflows in Azure Machine Learning (workspaces, model registry, endpoints. - Integrate Azure Cognitive Services (Language, Vision, Speech) and Azure OpenAI Service for enrichment, classification, summarization, and retrieval-augmented generation (RAG). - Orchestrate LLM applications using Azure ML pipelines, implementing guardrails, prompt versioning, and telemetry. - Deliver low-latency feature stores and micro-batch ingestion for ML and BI workloads. - Data modeling, quality, and observability - Define canonical and dimensional models; enforce standards (naming, lineage, SCD patterns) across marts and semantic layers (e.g., Power BI/Fabric). - Security, compliance, and governance (MCP best practices) - Apply Azure RBAC, Managed Identities, Private Endpoints, Key Vault, and Customer-Managed Keys; enforce policy with Azure Policy and Defender for Cloud. - Performance, reliability, and FinOps - Tune Databricks compute, caching, partitioning, Z-order, and query plans; optimize storage tiers and autoscaling. - Monitor SLOs/SLIs with Azure Monitor, Log Analytics, and custom metrics; build cost dashboards and alerts for proactive FinOps. - Collaboration, enablement, and leadership - Partner with business units on projects to define scope and deliverables; enable self-service via curated datasets and semantic models. - Mentor engineers on Microsoft stack best practices; contribute to standards, templates, and reusable components aligned with Microsoft certifications (e.g., Azure Data Engineer, Azure AI Engineer). Required Skills & Qualifications - Bachelor’s or Master’s degree in Computer Science, Engineering, or related field. - 5+ years of experience in data engineering or AI/ML production systems. - Advanced proficiency in Databricks and at least one programming language (Python, Scala, or Java). - Knowledge in implementing, fine-tuning, and deploying LLMs. - Strong capabilities in API development, version control, unit testing, and documentation. - Microsoft Certified: Azure Data Engineer Associate (DP-203) and/or Azure AI Engineer Associate (AI-102) strongly preferred; MCP/MCSA/MCSE or equivalent legacy Microsoft certifications a plus. - Hands-on experience with modern data pipeline orchestration tools (Azure Data Factory). - Deep knowledge of Azure data and AI services (Azure Data Lake, Azure Machine Learning, Azure Cognitive Services, Azure OpenAI). - Strong understanding of data modeling, warehousing, and data lake architecture. - Experience with DevOps practices and version control (Azure DevOps, Git, CI/CD). - Excellent communication and collaboration skills. - Microsoft Certified Professional (MCP) or relevant Azure certifications (e.g., Azure Data Engineer Associate, Azure AI Engineer Associate) are highly preferred. - Mentor Data Analytics Team members with best practices in the data space. - Current with industry trends in data engineering, Azure AI, and cloud platforms. Preferred Skills - Experience deploying machine learning models to production using Azure ML. - Exposure to real-time data streaming (Azure Event Hubs, Kafka). - Exposure to Model Context Protocol (MCP) and AI agents. Benefits: *Note that pay may vary based on location, skills, and experience. We offer a comprehensive benefits package for full time employees which generally includes: - Medical, dental, and vision plans - An opportunity to contribute to a Health Savings Account (HSA) - Tax-advantaged commuter benefits - Employee assistance program - Sick time, paid holidays and vacation in accordance with company policy and state law - Accident and life insurance as well as short- and long-term disability - 401(k) plan with company match, based on eligibility This position may also be eligible to receive a variable annual bonus based on company, team, and/or individual performance results in accordance with company policy. If a bonus applies, more information will be given at offer. All qualified applicants will receive consideration for employment without regard to age, race, creed, color, national origin, ancestry, marital status, affectional or sexual orientation, gender identity or expression, disability, nationality or sex. Qualified applicants who have access to or contact with students or the public, who are responsible for the safeguarding of others’ well-being, and who work with little supervision in close proximity to others will be required to complete a criminal history check once a contingent offer of employment is made. Applicants with arrest or conviction records will be considered for employment in accordance with local law. The nature and gravity of an offense, the length of time since the conviction, and the nature of the job in question are all considered, and criminal convictions do not automatically disqualify employment. Any discussion of criminal history will occur only after the background check is completed and a copy is provided to the applicant.

• Implementation and maintenance of the CDP environment (collector, enrich, loaders) • Integration of event data from various sources • Configuration and development of the CDP (schema repository) • Building and maintaining data pipelines in the cloud (AWS) • Creating and developing analytical models and integration with the data catalog • Participating in the development and implementation of user identification mechanisms (ID stitching, cross-device, cross-site, consent logic) • Documentation and collaboration with Data Engineering, Data Management, Data Governance, IT, Privacy, and Analytics teams