Data Engineering Manager

Cinemark•Plano, TX

About The Position

Join Our Team As part of our Cinemark Universe, you'll discover fun opportunities with real growth potential and plenty of perks. With 500+ theatres and nearly 6,000 screens; we're truly a global presence of 20,000 movie lovers working together to make unforgettable experiences. Role Summary: The Data Engineering Manager is a hands-on technical leader responsible for directing the design, development, and execution of our enterprise data architecture and engineering strategies. In this role, you will bridge the gap between high-level architectural vision and engineering delivery, acting as the primary driver for data pipeline execution. You will manage and build scalable data warehouses, optimize ingestion routines, and deliver robust BI/analytics solutions leveraging Microsoft Azure technologies. As a subject matter expert, you will establish and enforce architecture, Microsoft Fabric, DevOps, security, reliability, data quality, observability, and production-readiness standards while ensuring those standards are practically implemented through engineering delivery. The role will also drive AI enablement across Data Engineering and the analytics ecosystem, identifying and implementing capabilities that improve data discovery, insight generation, natural-language interaction, and the overall business-user experience.

Requirements

Bachelor’s degree in computer science, Engineering, Mathematics, or a related field (master’s degree preferred).
8+ years of hands-on data engineering, data architecture, solution design, and development experience, with at least 2+ years of providing technical leadership.
Candidates must demonstrate recent hands-on development experience and the ability to independently design, build, troubleshoot, and optimize enterprise data solutions.
5–7 years of advanced SQL experience, T-SQL, Python, and PySpark, including expert-level query performance tuning for data integration and consumption.
5+ years of hands-on experience with schema design, Data Vault, and dimensional data modeling techniques for data warehouse/mart consumption.
Strong experience designing, building, and maintaining data processing systems within Microsoft data technologies (Synapse, Fabric, Power BI, and Azure DevOps).
Proficient in sourcing data from diverse environments (REST web services, MS SQL Server) utilizing version control tools (Git).
Deep understanding of modern BI, analytics landscapes, and IT operations in high-availability environments.
Advanced level of SQL and query performance tuning techniques for Data Integration and Consumption
Experience with or knowledge of Agile Software Development methodologies
Communication skills and ability to develop and present solutions to all levels of management
Must be able to interact effectively and patiently with customers especially while under pressure
The ability to work on multiple projects/tasks simultaneously to meet project deadlines for self and others as required
Ability to establish and maintain positive working relationships with other employees.
Passion for delivering highly available, robust BI solutions
Knowledge of best practices and IT operations in an always-up, always-available service
Demonstrated ability in managing, scoping, and communicating data warehouse plans to internal clients and all levels of management.
Strong analytical and problem-solving skills with strict attention to accuracy, detail, and data-driven decision-making.
Exceptional communication skills, emotional intelligence, and the patience to guide teams and interact with customers under pressure.
Proven track record of fostering collaborative, positive working relationships across engineering and business units.

Nice To Haves

master’s degree preferred
Certified Data Management Professional (CDMP)
Data Vault 2.0 Certification
Microsoft Certified: Azure Data Engineer Associate
Microsoft Certified: Fabric Analytics Engineer

Responsibilities

Act as a hands-on technical manager, personally designing, developing, testing, troubleshooting, and optimizing enterprise data solutions.
Lead enterprise data architecture and technical design, establishing scalable architecture patterns, engineering standards, and guardrails across Microsoft Fabric, data platforms, integration, modeling, security, and analytics.
Develop and review SQL, T-SQL, Python, PySpark, dbt, data pipelines, Data Vault models, dimensional models, and Microsoft Fabric solutions as part of day-to-day delivery.
Lead by example through hands-on development and technical problem solving, particularly for complex, high-impact, or performance-critical solutions.
Serve as the technical authority for enterprise data architecture and Microsoft Fabric, establishing target architecture, solution standards, design patterns, and technical guardrails.
Conduct architecture, design, and code reviews, ensuring engineering solutions meet scalability, performance, security, maintainability, and reliability standards.
Establish Microsoft Fabric platform standards covering workspace/capacity architecture, security, performance, scalability, and cost optimization.
Establish and enforce DevOps standards including Git, branching, CI/CD, automated deployments, release management, and environment promotion.
Define and implement data quality, observability, monitoring, alerting, SLA, and production-readiness standards.
Troubleshoot and resolve complex production, performance, data quality, and platform issues, providing technical direction for root-cause resolution and prevention.
Drive AI enablement across data engineering and analytics, improving development productivity, automation, testing, troubleshooting, data quality, and operational efficiency.
Enable AI-powered Power BI experiences through natural-language interaction, intelligent insight discovery, assisted analysis, and easier access to trusted enterprise data.
Evaluate and implement emerging Microsoft Fabric, Power BI, Copilot, and AI capabilities, establishing governed and reusable patterns for enterprise adoption.
Mentor engineers through pairing, code reviews, design reviews, technical guidance, and hands-on engineering collaboration.