Pay
$127K–$190K is typical
The middle half of what similar US postings state. This one doesn’t list pay.
From 2,133 postings in the last year. Stated ranges, not salaries paid.
CORP - Cinemark Service Center, Plano, TX
Open 4 months, first seen by us 137 days agoEmployment type in the employer’s posting: Full timeFrom the employer’s posting
The Senior Data Engineer is a hands-on technical role responsible for designing, developing, testing, deploying, and supporting scalable enterprise data solutions.
The Senior Data Engineer will also help drive AI enablement across Data Engineering and the analytics ecosystem by applying AI-assisted engineering capabilities, improving data discovery and insight generation, and enabling better natural-language and AI-powered experiences in Power BI and related analytics solutions.
Design, build and optimize enterprise data pipelines on Microsoft Fabric and Azure
Develop Bronze, Silver and Gold data layers and dbt models
Build data quality controls, monitoring and observability for pipelines
Troubleshoot production pipeline failures and perform root-cause analysis
Migrate legacy ETL and warehouse workloads to Microsoft Fabric
The Senior Data Engineer is a hands-on technical role responsible for designing, developing, testing, deploying, and supporting scalable enterprise data solutions. The role will build and optimize data pipelines, data models, and analytics-ready data products using Microsoft Fabric and Azure technologies while ensuring strong engineering, security, reliability, data quality, observability, and production-readiness standards.
The Senior Data Engineer will also help drive AI enablement across Data Engineering and the analytics ecosystem by applying AI-assisted engineering capabilities, improving data discovery and insight generation, and enabling better natural-language and AI-powered experiences in Power BI and related analytics solutions.
Design, develop, test, deploy, troubleshoot, and optimize enterprise data pipelines and data solutions using Microsoft Fabric, Azure, SQL, Python, Spark, and related technologies.
Develop and maintain Bronze, Silver, and Gold data layers
Build data quality controls, reconciliation processes, monitoring, alerting, lineage, and observability
Support production operations by troubleshooting pipeline failures, performance issues, data defects, and critical incidents; perform root-cause analysis and implement permanent fixes.
Support migration and modernization of legacy ETL and enterprise data warehouse workloads to Microsoft Fabric
Bachelor’s degree in computer science, Engineering, Math or related field is required Master's degree is preferred
Communication skills and ability to develop and present solutions to all levels of management
5+ years of experience in data engineering, data warehousing, ETL/ELT, or enterprise analytics platforms, with demonstrated experience delivering production-grade data solutions.
Ability to establish and maintain positive working relationships with other employees.
Experience with Microsoft Fabric, Azure Data Factory, Azure Data Lake Storage, Synapse, Databricks, or comparable modern cloud data platforms.
Knowledge of best practices and IT operations in an always-up, always-available service
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.
Requirements: - Bachelor’s degree in computer science, Engineering, Math or related field is required Master's degree is preferred - 5+ years of experience in data engineering, data warehousing, ETL/ELT, or enterprise analytics platforms, with demonstrated experience delivering production-grade data solutions.
Open 4 monthsWe first saw this posting 137 days ago and it is still up. Roles open this long are often slow to fill or kept open to collect applications.
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
$127K–$190K is typical
The middle half of what similar US postings state. This one doesn’t list pay.
From 2,133 postings in the last year. Stated ranges, not salaries paid.
Day 137
Up longer than most. Similar jobs usually come down between day 6 and day 54.
From 11,283 similar postings that came down. Coming down is not always a hire.
2 open jobs
Open jobs by the week we first saw them, last 12 weeks.
Hiring recordAdd your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
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.
- 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/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 AI, machine learning, natural-language querying, and advanced analytics use cases.
- 5+ years of experience in data engineering, data warehousing, ETL/ELT, or enterprise analytics platforms, with demonstrated experience delivering production-grade data solutions. - Strong hands-on SQL skills and experience with Python and/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.
- 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.
Role Summary: The Senior Data Engineer is a hands-on technical role responsible for designing, developing, testing, deploying, and supporting scalable enterprise data solutions. The role will build and optimize data pipelines, data models, and analytics-ready data products using Microsoft Fabric and Azure technologies while ensuring strong engineering, security, reliability, data quality, observability, and production-readiness standards. The Senior Data Engineer will also help drive AI enablement across Data Engineering and the analytics ecosystem by applying AI-assisted engineering capabilities, improving data discovery and insight generation, and enabling better natural-language and AI-powered experiences in Power BI and related analytics solutions.
- Strong hands-on SQL skills and experience with Python and/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/lakehouse patterns, and enterprise data architecture concepts.
- Develop and maintain Bronze, Silver, and Gold data layers and implement enterprise modeling patterns, including Data Vault 2.0 and dimensional/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.
- 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.
The Senior Data Engineer is a hands-on technical role responsible for designing, developing, testing, deploying, and supporting scalable enterprise data solutions. The role will build and optimize data pipelines, data models, and analytics-ready data products using Microsoft Fabric and Azure technologies while ensuring strong engineering, security, reliability, data quality, observability, and production-readiness standards. The Senior Data Engineer will also help drive AI enablement across Data Engineering and the analytics ecosystem by applying AI-assisted engineering capabilities, improving data discovery and insight generation, and enabling better natural-language and AI-powered experiences in Power BI and related analytics solutions. Responsibilities:
- Implement security, access controls, data protection, and governance requirements in partnership with architecture, governance, and security teams. - Work closely with BI, 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.
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New Data Engineer postings at the employers we follow are up 8% over the last 5 weeks compared with the 5 before.
Each bar is one week of new postings. The darkest bars are the last 5 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
We file this job under Data Engineer, by the work the posting describes.
Data engineers build and run the pipelines that copy data out of apps and outside services into a warehouse or lake, and fix them when a source changes or a load fails.
Expect SQL, Python, a cloud platform, a scheduler such as Airflow, and often tools for large data such as Spark or Kafka.
An analytics engineer works one step later, turning the raw data a data engineer lands into clean tables people can query.
The government has no code for data engineers, so these figures are for the closest group, database architects, which includes data integration and data warehousing specialists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1243.
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Role Summary:
The Senior Data Engineer is a hands-on technical role responsible for designing, developing, testing, deploying, and supporting scalable enterprise data solutions. The role will build and optimize data pipelines, data models, and analytics-ready data products using Microsoft Fabric and Azure technologies while ensuring strong engineering, security, reliability, data quality, observability, and production-readiness standards.Responsibilities:
Requirements:
Preferred Skills:
Benefits Available:
At Cinemark, we believe every team member should feel like a hero. Each career comes with a variety of blockbuster benefits for both hourly and salaried team members.
*Benefits may vary by career category, so be sure to check the specific details on our career site.
DISCLAIMER: This job description is intended only as a general guideline of your duties and responsibilities at Cinemark and is not a legally binding contract. Cinemark reserves the right to amend, change or terminate the job description, as it deems appropriate. Any change amendments, or modifications may be implemented even though they have not been communicated, reprinted or substituted in this job description.
Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.
Cinemark is an Equal Opportunity Employer
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CORP - Cinemark Service Center, Plano, TX
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