AgileEngine is an Inc. 5000 company that creates award-winning software for Fortune 500 brands and trailblazing startups across 17+ industries. We rank among the leaders in areas like application development and AI/ML, and our people-first culture has earned us multiple Best Place to Work awards.
WHY JOIN US
If you're looking for a place to grow, make an impact, and work with people who care, we'd love to meet you!
ABOUT THE ROLE
We are looking for a Senior Data and Analytics Engineer to sit with business stakeholders and translate their needs into data transformation work using dbt and SQL.
WHAT YOU WILL DO
- Deliver robust data features and pipelines directly within project teams, focusing on fast-paced, business-facing verticals like distribution. Accommodate rapid reprioritization in a process-light environment without being siloed in a fixed-scope pool.
- Translate complex business use cases into robust data models using dbt and SQL. Tackle rigorous business logic, such as aggregating revenue and performance data from platforms like Tubi, Roku, YouTube, and Amazon channels, and joining it with internal contracts.
- Build and maintain scalable pipelines utilizing a technical stack that includes Snowflake cloud warehouse, dbt Cloud, GitHub, VS Code, and local Python. Transition project documentation from tribal knowledge into dbt catalogs.
- Leverage AI tools within the development workflow, including GitHub Copilot, Microsoft Copilot, Snowflake Cortex, and dbt wizard features. Collaborate with technical leadership to uplevel the adoption of these tools within specific governance setups.
- Partner effectively with product managers, data visualization leads, and strategic analysts to evaluate requests and deliver consumption-ready data. Collaborate directly with technical leadership on technical decisions and quality standards.
MUST HAVES
- 4+ years of experience in data engineering or analytics engineering within a production environment.
- Expert-level Python and SQL skills.
- Extensive hands-on experience building transformation pipelines in dbt Cloud is strongly preferred.
- Strong proficiency with modern cloud data platforms, specifically Snowflake, as well as development tools like GitHub and VS Code.
- Proven ability to thrive in a process-light environment that operates more like a data science team than a highly tuned software engineering team.
- Strong communication skills to effectively collaborate with non-technical stakeholders and product managers during bi-weekly or monthly sprint planning.
NICE TO HAVES
- Deep domain expertise in the media and entertainment industry, specifically Hollywood studios.
- Hands-on experience with specific media data challenges, including title matching and metadata enrichment.
- Familiarity with AI-driven development tools, such as Snowflake Cortex and GitHub Copilot, and an understanding of the governance and grants required to manage them.
PERKS AND BENEFITS
- Professional growth: Accelerate your professional journey with mentorship, TechTalks, and personalized growth roadmaps.
- Competitive compensation: We match your ever-growing skills, talent, and contributions with competitive USD-based compensation and budgets for education, fitness, and team activities.
- A selection of exciting projects: Join projects with modern solutions development and top-tier clients that include Fortune 500 enterprises and leading product brands.
- Flextime: Tailor your schedule for an optimal work-life balance, by having the options of working from home and going to the office – whatever makes you the happiest and most productive.
Requirements
Experience: 4+ years in data engineering or analytics engineering within a production environment. Technical Acumen: Expert-level Python and SQL skills. Extensive hands-on experience building transformation pipelines in dbt Cloud is strongly preferred. Data Platforms: Strong proficiency with modern cloud data platforms, specifically Snowflake, as well as development tools like GitHub and VS Code. Agile Adaptability: Proven ability to thrive in a process-light environment that operates more like a data science team than a highly tuned software engineering team. Communication: Strong communication skills to effectively collaborate with non-technical stakeholders and product managers during bi-weekly or monthly sprint planning.