• Own Mixbook’s data platform end-to-end, including ingestion, orchestration, transformation, and the Redshift data warehouse • Establish clear accountability, SLAs, and standards for critical datasets and business metrics • Stabilize and harden fragile pipelines, reducing data incidents and reactive firefighting • Define and enforce best practices for dbt modeling, data quality, and metric consistency. Deliver analytics-ready models that power Looker and downstream use cases. • Partner closely with Platform Engineering, Product Engineering, Data Analytics, and business stakeholders across Marketing, Product, Operations and Finance to align on priorities and tradeoffs • Act as the primary point of contact for data reliability and warehouse health at the executive level • Make pragmatic build vs. buy decisions and resist unnecessary replatforming or tool churn • Lead by building. Write and review production data engineering code. Set technical standards and architectural direction. • Enable faster, more confident analytics and experimentation by increasing trust in data • Set the stage for future data science, ML and AI capabilities once foundations are solid

• Write and deploy crawling scripts to collect source data from the web • Write and run data transformers in Scala Spark to standardize bulk data sets • Write and run modules in Python to parse entity references and relationships from source data • Diagnose and fix bugs reported by internal and external users • Analyze and report on internal datasets to answer questions and inform feature work • Work collaboratively on and across a team of engineers using basic agile principles • Give and receive feedback through code reviews

• 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.