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First seen by Alion on Nov 8, 2026. Deloitte scores A on the Alion truth index.

Overview
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Deloitte is one of the "Big Four" global accounting and professional services firms, providing audit, tax, consulting, and risk advisory services to organizations worldwide. Founded in London in 1845, it operates as a multinational network of independent member firms spanning over 150 countries and territories. Known for its extensive market reach and industry expertise, the organization serves a vast majority of the Fortune Global 500 companies.

Job description:


The Music Supply Chain fleet oversees products and optimizes workflows that enable users to manage both publishing and recorded music businesses-from acquisition and distribution to administration and monetization-leveraging analytics to drive data-informed decision making.


Job Summary:


As a Software Engineer, you will architect and deliver resilient, scalable systems across our music supply chain applications. This role blends hands-on technical leadership with strategic influence-transforming business requirements into innovative solutions that support music supply chain platform and data integrations.


This position might be a great fit if you:

  • Are a curious and efficient engineer who wants to help shape the direction of development and collaborate closely with some of the brightest minds in our organization.
  • Thrive in an agile, collaborative environment where teamwork and innovation are valued.


In this role, you'll work within the Music repertoire, planning, distribution and sales focusing on data streams and integrations between systems and various upstream and downstream applications. You'll collaborate closely with multiple internal and external teams to design, implement, and maintain robust data integration capabilities that ensure accuracy, scalability, and efficiency across the music supply chain.


Responsibilities and Duties of the Role:

  • Technical Expertise: Possesses comprehensive knowledge of technologies and leads architectural design and implementation of large projects. Fixes critical bugs and drives technical excellence across teams. Creates and reviews complex solutions and ensures alignment with organizational standards.
  • Influence and Leadership: Mentors senior engineers and facilitates collaboration across teams. Influences and drives cross-functional team collaboration with teams like PM, QA, and Design. Mediates disagreements and drives alignment among stakeholders. Builds relationships within engineering and with cross-functional partners and encourages knowledge sharing. Leadership is both technical and interpersonal, shaping team culture and performance.
  • Ownership & Scope: Owns and leads development projects with multiple components and teams. Sets architectural direction and ensures scalability and maintainability. Decisions significantly influence project and team outcomes. Scope includes large-scale solutions and strategic planning.
  • Impact: Broadly influences product and project success across teams. Contributions are measured by achievement of customer and operational objectives and OKRs. Work has material impact on business outcomes. Regularly drives innovation and technical strategy.


Required Education, Experience/Skills/Training:

  • 5+ years of experience in a software engineering role, with a strong track record of designing, developing, and delivering production-grade applications.
  • Strong proficiency in Python, with the ability to write efficient, maintainable, and testable code.
  • Hands-on experience with Apache Spark and related file formats (Avro, Parquet, JSON, etc.) for large-scale data processing.
  • Advanced knowledge of SQL, including data modeling, schema design, relational database concepts, query optimization, and performance tuning.
  • Expertise with data platform technologies such as Databricks, Snowflake, and orchestration frameworks like Apache Airflow (or similar tools).
  • Deep understanding of data integration concepts and ETL/ELT pipeline design, including ingestion, transformation, and delivery of data across systems.
  • Experience with containerization and DevOps practices, including GitLab, CI/CD pipelines, Docker, and Kubernetes.
  • Strong knowledge of cloud environments, preferably AWS (e.g., S3, RDS, Lambda, SQS/SNS, VPC, etc.).
  • Solid understanding of data lakehouse and microservices architectures, with experience in designing and maintaining scalable, modular systems.
  • Experience integrating with APIs (RESTful, GraphQL) and handling data streaming or messaging frameworks such as Kafka, Kinesis, or Pub/Sub.
  • Proficiency with Linux environments and shell scripting (bash) for automation and maintenance tasks.
  • Strong grasp of object-oriented and functional programming paradigms, and the ability to apply them to real-world data engineering problems.
  • Understanding of data governance, security, and observability best practices, including logging, monitoring, and alerting for data pipelines.
  • Excellent communication, collaboration, and problem-solving skills, with the ability to work effectively across teams.
  • Strong time management and organizational skills, capable of breaking down complex problems into actionable tasks.
  • Experience working in Agile environments, contributing to iterative development, sprint planning, and continuous improvement.
  • Bachelor's degree in computer science, Information Systems, Software, Electrical or Electronics Engineering, or comparable field of study, and/or equivalent work experience.


Preferred Qualifications:

  • AWS (advanced cloud services and infrastructure management)
  • Kafka (real-time data streaming and event processing)
  • Apache Airflow (workflow orchestration and data pipeline management)
  • Databricks (data engineering, analytics, and machine learning workflows)
  • Snowflake (cloud data warehousing and analytics)
  • PostgreSQL (advanced database features and performance tuning)
  • Serverless computing (e.g., AWS Lambda or similar event-driven architectures)

Skills

Airflow, Apache Spark, Databricks, ELT, ETL, Kafka, Python, Spark

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