C

Cinemark Theatres

Operates multiplex theaters and screenings

Senior Data Engineer

Data EngineeringConfirmed live in the last 24 hours
Full-timePlano, TX, USANo salary listedIn-person

About the Job

Requirements

  • A bachelor's degree in computer science, engineering, mathematics, or a related field is required; a master's degree is preferred.
  • At least 5 years of experience in data engineering, data warehousing, ETL/ELT, or enterprise analytics platforms, including delivery of production-grade data solutions.
  • Strong hands-on SQL skills and experience with Python or PySpark for data engineering workloads.
  • Experience with Microsoft Fabric, Azure Data Factory, Azure Data Lake Storage, Synapse, Databricks, or comparable modern cloud data platforms.
  • Strong understanding of data modeling, dimensional modeling, data lake and lakehouse patterns, and enterprise data architecture concepts.
  • Experience implementing data quality, monitoring, observability, automated testing, and production support practices.
  • Experience with Git, continuous integration and continuous delivery, DevOps, and automated deployment practices.
  • Strong analytical, troubleshooting, communication, and cross-functional collaboration skills.
  • Experience with or knowledge of Agile software development methodologies.
  • Ability to learn new technologies and analytics techniques.
  • Ability to develop and present solutions to all levels of management.
  • Ability to interact effectively and patiently with customers, especially under pressure.
  • Ability to work on multiple projects or tasks simultaneously and meet project deadlines for self and others as required.
  • Ability to establish and maintain positive working relationships with other employees.
  • Strong analytical and problem-solving skills, strict attention to accuracy and detail, and ability to evolve data into knowledge.
  • Ability to deliver highly available, robust business intelligence solutions.
  • Knowledge of best practices and IT operations in an always-up, always-available service.

Responsibilities

  • Design, develop, test, deploy, troubleshoot, and optimize enterprise data pipelines and data solutions using Microsoft Fabric, Azure, SQL, Python, Spark, and related technologies.
  • Build scalable ingestion, transformation, and data processing frameworks for batch and near-real-time workloads across multiple enterprise data sources.
  • Develop and maintain Bronze, Silver, and Gold data layers and implement enterprise modeling patterns, including Data Vault 2.0 and dimensional or curated models where appropriate.
  • Develop and maintain dbt models, reusable transformation frameworks, documentation, automated tests, and engineering standards.
  • Partner with technical leadership to implement enterprise data architecture patterns, engineering standards, reusable frameworks, and platform guardrails.
  • Implement continuous integration and continuous delivery, source control, automated testing, deployment pipelines, and DevOps practices for data engineering solutions.
  • Build data quality controls, reconciliation processes, monitoring, alerting, lineage, and observability to proactively identify and resolve data issues.
  • Support production operations by troubleshooting pipeline failures, performance issues, data defects, and critical incidents; perform root-cause analysis and implement permanent fixes.
  • Optimize data pipelines, SQL queries, Spark workloads, storage, and compute utilization for performance, scalability, reliability, and cost efficiency.
  • Implement security, access controls, data protection, and governance requirements in partnership with architecture, governance, and security teams.
  • Work with business intelligence, analytics, and business teams to deliver trusted, analytics-ready data products and support Power BI semantic models and reporting solutions.
  • Support migration and modernization of legacy ETL and enterprise data warehouse workloads to Microsoft Fabric while ensuring reconciliation, business continuity, and production readiness.
  • Maintain technical documentation, including solution designs, data mappings, operational runbooks, support procedures, and production-readiness artifacts.
  • Apply AI-assisted engineering capabilities to improve developer productivity, accelerate SQL and Python development, support code quality, automate documentation and testing, and improve troubleshooting and root-cause analysis.
  • Enable AI-ready data products by ensuring data is trusted, well-modeled, governed, documented, and accessible for artificial intelligence, machine learning, natural-language querying, and advanced analytics use cases.

Desired Qualifications

  • Hands-on experience with Microsoft Fabric, OneLake, Fabric Data Engineering, Fabric Data Factory, and related platform capabilities.
  • Experience with dbt Core and Data Vault 2.0.
  • Experience with Microsoft Purview, metadata management, lineage, governance, and data catalog capabilities.
  • Exposure to artificial intelligence and machine learning, generative artificial intelligence, Microsoft Copilot capabilities, or AI-assisted data and analytics engineering.

About the Company

Cinemark Theatres

Operates multiplex theaters and screenings

Cinemark Theatres operates a chain of movie theaters in the United States and Latin America, showing films and offering snacks and related experiences. It earns revenue from ticket sales, concessions, and advertising, and it manages showtimes, seating, and theater upkeep. The company grows by building new theaters and acquiring other chains, expanding its geographic footprint. Its goal is to become a leading global movie exhibitor by expanding its theater network and strengthening its financial position.

Company size
10,001+
Company stage
IPO
Headquarters
Dallas, TX
Founded
1984

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