Principal Engineer

Waste Management, Inc. (WM)•Houston, TX

10d•Onsite

About The Position

The Principal Software Engineer within the Data Services (Corporate) team is a principal-level technical role responsible for designing, developing, and optimizing enterprise data solutions. This position focuses on building and maintaining scalable, reliable, and secure data systems that support business operations and analytics. The Principal Software Engineer undertakes highly complex projects that require additional specialized technical expertise, applies advanced software engineering practices, works with modern data platforms (Snowflake, AWS, DBT, etc.), and ensures that solutions adhere to enterprise standards. While the primary focus is on engineering and solution delivery, the role also requires knowledge of data architecture principles and business analysis practices to effectively collaborate with architects, analysts, and stakeholders. This combination ensures that technical solutions are aligned with business needs and long-term data strategy.

Requirements

Bachelor's Degree (accredited) in Computer Science, MIS, or similar area of study.
10+ years of previous experience required (in addition to education requirement).
Expert-level with data engineering expertise, including ETL, data warehouses, marts, and lake development
Expert-level experience working with SQL relational and NoSQL databases, query authoring (SQL) as well as working familiarity with a variety of databases
Expert-level experience working with Cloud Data Warehouse like Snowflake, IBM PureData, Google BigQuery, Amazon Redshift
Expert-level experience working with AWS cloud services: ASW Glue, EC2, S3, Lambda, SQS, SNS, etc.
Expert-level experience working with GitHub, CI/CD and its integration with the ETL tools for version control
Expert-level experience working with Informatica PowerCenter, various scripting languages, SQL, querying tools
Expert-level experience working with modern data management tools and platforms, including Spark, NoSQL, APIs, Streaming, and other analytic data platforms
Proficient level experience in data observability
Proficient level experience in Agile/Scrum project management and product ownership
Expert level in enterprise data management, integration patterns, and metadata practices
Expert level to apply architecture and analysis knowledge when working with cross-functional teams
Expert-level strong problem-solving skills with attention to detail and quality
Excellent communication skills for both technical and non-technical audiences
Proficient ability to lead, mentor, and collaborate within a high-performing engineering team
Proficient knowledge of project management/change management regarding acquisition/development life cycles
Expert level in systems development, implementation, upgrades, and analyses
Proficient in QA testing, catalyst or unified business modeling, system design, and analysis
Knowledge of enterprise coding standards
Expert level with hands-on experience in writing highly complex code
Ability to perform code reviews
Expert knowledge of software methodologies
Ability to learn new and emerging technologies
Ability to multitask, meet deadlines, and work in a fast-paced environment
Ability to adapt to change
Demonstrate flexibility and a willingness to undertake a wide variety of challenging tasks
General business knowledge and concepts

Responsibilities

Build data pipelines required for optimal extraction, transformation, and loading of data from a wide variety of data sources using Cloud Integration ETL/ELT tools including but not limited to Informatica, AWS Glue, DBT, etc., Cloud Data Warehouse including but not limited to Snowflake, Oracle, IBM PureData, SQL, Shell Scripting, Python, AWS technologies, GitHub, various scripting languages, data quality tools, and metadata management tools.
Design, develop and document ETL/ELT, event-driven data integration architecture solutions. Troubleshoot and tune complex SQL.
Presents, communicates, and articulates technical processes effectively to all levels of the organization (including technical and non-technical audiences, Senior Leadership, VPs and the C-level executives).
Contributes strategic vision and integrates a broad range of ideas regarding applications and software data development.
Work with the Business Analysts, Data Analysts, Data Architects, BI Architects, Data Scientists, and Data Product Owners to establish an understanding of source data, determine data transformation and integration requirements to align engineering solutions with enterprise data strategies and technical standards
Provide technical leadership in coding, testing, and code reviews; Mentors and fosters growth of peers and team members.
Support data quality, governance, data observability, and compliance through development of frameworks, metadata, and standards.
Apply engineering best practices to ensure performance, reliability, and scalability of enterprise data solutions.
Works with customers and technical staff to resolve problems with software and responds to suggestions for improvements and enhancements.
Participate in the creation of technical documentation, including data flows, integration specifications, and solution designs.
Stay current with emerging technologies in data management and AI. Recommend improvements to existing solutions.