Data Engineer
Waste Connections
The Woodlands, TX · Posted October 14, 2026
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Where The Woodlands, TX ranks
Where The Woodlands, TX placed in our monthly rankings, month by month. Each month stays online at its own address.
November 2026
- #7Best cities for mid-career professionals in the Southwest57% · of 44
- #10Best cities for entry-level jobs that want AI skills in the Southwest7% · of 39
- #16Cities with the most hybrid jobs in the Southwest9% · of 43
- #17Cities with the most jobs that need no experience in the Southwest1.2% · of 43
- #22Best cities for AI-skill jobs in the Southwest4% · of 44
- #22Best cities for director and executive jobs in the Southwest16% · of 44
Rankings about data & analytics jobs
- Best cities for data and analytics jobs #1 New York (1,713 openings)
- Best cities for data and analytics pay after cost of living #1 Foster ($232k)
- Most requested AI skills in data and analytics jobs #1 Machine learning engineering (17.1%)
- AI tools named most often in data and analytics jobs #1 Databricks (7.6%)
- Employers with the most data and analytics jobs #1 Amazon (711 roles)
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Pay compared with the market
This listing does not state pay. Across 152 open data engineer listings that state pay, the middle half runs $114,500 to $172,500 and the median is $140,000.
Listed pay is what employers advertise, not what people are paid.
How AI is used in this kind of work
Among database architects, AI is already used for a large share of the tasks. Measured exposure for database architects: 58% (high).
Share of this job’s tasks that AI is already used for at work, from real usage. It is not a forecast of job loss, and a low number means no use seen yet. Source: Anthropic Economic Index.
Skills this job asks for
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About the job
Data Engineer
About the Role
Waste Connections is seeking a talented Data Engineer to join our Enterprise Data & Analytics team.
This role is responsible for designing, building, and supporting modern cloud-based data solutions that enable reporting, analytics, and business decision-making across the organization. The ideal candidate will have experience developing scalable data pipelines, integrating data from multiple sources, and optimizing cloud data platforms.
You will work closely with business stakeholders, analysts, architects, and engineering teams to deliver reliable data products and help expand Waste Connections' data capabilities.
Key Responsibilities
Design, develop, and maintain scalable data pipelines using Databricks, Python, Spark, and SQL.
Build and support enterprise data lakehouse solutions on AWS.
Integrate and transform data from multiple internal and external sources.
Ensure data quality, reliability, security, and governance standards are met.
Optimize data processing workloads for performance and cost efficiency.
Develop and maintain data models that support reporting and analytics initiatives.
Implement CI/CD processes, automation, and Infrastructure-as-Code practices.
Monitor and troubleshoot data pipelines and platform performance issues.
Collaborate with cross-functional teams to deliver data solutions that support business objectives.
Qualifications
Required
Bachelor's degree in Computer Science, Information Systems, Engineering, or a related field.
2+ years of experience in Data Engineering, Cloud Engineering, or a related technical role.
Experience with AWS, Databricks, Python, and SQL.
Experience building and supporting ETL/ELT pipelines and modern data architectures.
Understanding of data modeling, data integration, and data governance concepts.
Strong analytical, problem-solving, communication, and collaboration skills.
Preferred
Experience with Apache Spark, Delta Lake, and large-scale data platforms.
Experience with Terraform, Infrastructure-as-Code, and cloud automation.
Familiarity with business intelligence and analytics environments.
AWS, Databricks, or related cloud certifications.
Waste Connections is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to disability or protected veteran status.