Associate Data Engineer

About Us

At Cast & Crew, we’ve empowered creativity and supported the global entertainment industry for decades. Together with our family of brands – Backstage, CAPS, Checks & Balances, Final Draft, Media Services, Sargent-Disc, and The TEAM Companies – we operate as a combined entertainment technology and services provider offering industry standard screenwriting accounting software, digital payroll products, data & reporting, and a host of creative tools.

The industry continues to move faster than ever, and the need for our expertise, our technology, and our people has never been greater. We are a production’s best ally every step of the way. #One Cast One Crew

We are looking for a Data Engineer to help design, build, and maintain data pipelines and ETL processes that power our payroll application platform. You will work with modern tools like Apache Kafka, Apache Spark, and Snowflake, collaborating with engineering and product teams to deliver reliable data solutions. This role offers an opportunity to learn data engineering, support the design, development, and maintenance of data pipelines and ETL processes that power our payroll application platform.

• Assist in building and maintaining data pipelines and support the development of ETL (Extract, Transform, Load) processes
• Help implement data ingestion workflows using tools like Apache Kafka
• Participate in code reviews, data validation and testing activities
• Write clean, maintainable code following team standards and conventions
• Support integration of payroll data and accounting systems data into Snowflake data lake
• Assist in mapping data fields between different systems and ensuring data quality
• Help monitor data pipelines for issues and support troubleshooting efforts
• Document data flows, transformations, and pipeline architectures
• Partner with product to translate business requirements into technical data solutions
• Participate in agile ceremonies including sprint planning, daily standups, backlog grooming, and retrospectives
• Support data requests from analytics, finance, and business intelligence teams
• Assist in implementing data quality checks and validation rules
• Help create and maintain automated tests and clear documentation for data pipelines, schemas, and processes
• Support monitoring and alerting systems for data pipeline health
• Participate in root cause analysis when data issues occur

• Bachelor's degree in Computer Science, Data Science, Information Systems, Engineering, or related field (or equivalent combination of education and experience)
• Basic programming skills in Python, node.js, Scala, or similar languages
• Foundational understanding of SQL and relational databases
• Familiarity with data structures, algorithms, and software engineering concepts
• Interest in learning big data technologies and distributed systems
• Strong analytical thinking and problem-solving abilities
• Excellent communication skills and ability to work in a team environment
• Detail-oriented with commitment to data quality and accuracy
• Eagerness to learn new technologies and adapt to changing requirements

• Exposure to Apache Kafka, Apache Spark for large-scale data processing
• Experience with ETL tools or frameworks (Airflow, Luigi, dbt, Talend, Informatica)
• Knowledge of data pipeline orchestration and workflow management
• Coursework or projects involving data warehousing or data lakes
• Understanding of cloud platforms (AWS, Azure, GCP) and their data services
• Familiarity with containerization (Docker) and orchestration (Kubernetes)
• Experience with data modeling and schema design
• Knowledge of No
  
  SQL databases (Mongo
  
  DB, Cassandra, Dynamo
  
  DB)
• Exposure to CI/CD practices and Dev Ops principles
• Understanding of data governance and compliance concepts

• Sedentary – Involves sitting most of the time but may involve walking or standing for brief periods of time. Some positions may entail exerting up to 15 lbs. of force occasionally and/or a negligible amount of force to lift, carry, push, or pull.

Gain hands-on experience with modern data engineering tools, mentorship from senior…