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D’Addario & Company is the largest manufacturer and distributor of musical instrument accessories in the world. As a US based manufacturing company, we pride ourselves on high automation machinery and innovative technology, as well as our commitment to environmentally sustainable practices. Through our work with the D'Addario Foundation we are committed to helping make music education accessible and ensuring hundreds of thousands of students can participate in music-making programs worldwide, regardless of instrumentation, genre, or life circumstance. Most importantly, we pride ourselves on our diverse team of individuals who commit to the embodiment of our core values of curiosity, passion, candor, family and responsibility and translate them into action every day. The Business Intelligence team is looking for a hands-on Data Analytics Engineer to help build, transform, and optimize D’Addario’s global data infrastructure. In this role, you’ll design and maintain production-grade data pipelines while modeling the clean, well-tested, and documented datasets that power reporting and self-service analytics across the company. You’ll work closely with the Global Director of BI and our analysts to turn raw data into reliable, business-ready data products. This is an ideal opportunity for an engineer who thrives at bringing data into order , enjoys solving complex data challenges, and is passionate about enabling organizational data intelligence. At D’Addario, we don’t just offer a job—we offer a career with one of the most iconic names in the music industry. We’re passionate about innovation, craftsmanship, and creating a workplace where diverse backgrounds, perspectives, and ideas thrive. We’re eager to connect with individuals who bring fresh thinking and a collaborative spirit. If you’re ready to make an impact, we’d love to hear how you’ll add value to our team. Some Perks & Benefits of Working at D'Addario: 401(k) Retirement Plan: Once eligible, D’Addario provides an employer Safe Harbor contribution of 3% of total annual earnings, with the opportunity to earn up to an additional 7% in employer Discretionary contributions, regardless of employee contribution level Health, vision, and dental insurance 12 weeks of fully paid parental leave Fertility and family-building benefits Annual performance and compensation reviews Career pathing and professional development via LinkedIn Learning A generous allotment of Paid Time Off (PTO) days Flexible sick day policy 12 paid holidays Life and AD&D insurance Enhanced short-term disability insurance Employee Assistance Program (EAP) Tuition reimbursement Discounts on D’Addario products and merchandise Company jam nights, artist performances, holiday parties, and special events A passionate, talented team that loves what they do! Compensation: We offer a competitive total compensation package. The base salary range for this role is $115,000-$130,000 and is commensurate with experience, skills, and qualifications. This position is eligible for a discretionary annual bonus, in accordance with company policy. Responsibilities Build & Optimize Pipelines: Design, implement, and maintain robust, high-performance ELT/ETL data pipelines within Microsoft Fabric and our broader data environment. Data Integration: Connect and harmonize new data sources—including ERP, e-commerce platforms, and external APIs—into a centralized data platform. Analytics Data Modeling: Transform raw data into clean, well-structured dimensional models, data marts, and reusable datasets (star schemas) that are analysis-ready for reporting and self-service BI. Semantic Layer & Metrics: Build and maintain semantic models and standardized metric definitions in Power BI and Microsoft Fabric so the business works from a single, trusted source of truth. Data Quality & Testing: Implement automated testing, validation, and monitoring to ensure pipelines and datasets are accurate , reliable, and well-documented. Collaboration: Partner with analysts and stakeholders across Sales, Marketing, Operations, and Product to translate business requirements into reliable data products. Continuous Improvement: Follow and help improve team standards for coding, documentation, version control, and DataOps across our data engineering and analytics workflows. Qualifications 3+ years of hands-on experience as a Data Engineer, Analytics Engineer, or equivalent Experience building and maintaining production-grade data pipelines and analytics data models Proficiency in Python, PySpark , and SQL Bachelor's degree in Computer Science , Engineering, Data Science, or related field (or equivalent professional experience) Preferred experience with Microsoft Fabric, Azure Synapse, or Azure Data Lake Preferred experience implementing DataOps best practices and building transformation models with dbt or similar frameworks Familiarity with API integrations and third-party data ingestion Knowledge of data governance and data quality frameworks Musician or passion for music a plus Knowledge, skills, & abilities: Strong programming in Python and PySpark for data processing and transformation Advanced SQL and dimensional data modeling (e.g., star schema / Kimball) for analytical performance and scalability Experience building and maintaining ELT/ETL pipelines and transformation layers, including automated testing and validation of analysis-ready datasets Strong understanding of cloud data platforms (Azure preferred) Excellent communication skills with the ability to simplify complex technical concepts Familiarity with semantic modeling and BI tools such as Power BI and Microsoft Fabric Self-directed, highly organized, and comfortable operating in a fast-paced, evolving environment Passion for innovation and leveraging data to create business impact
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.