Senior Lead Engineer
Indexed description
We are looking for humble geniuses, who believe that engineering has the potential to make the impossible possible; innovators, who are not only inspired by technology and innovation, but also perpetually driven to design, develop, and test as a trusted partner for Fortune 500 customers. As a team of remarkably diverse engineers, we recognize that what we are really engineering is a brighter future for us all. If you want to contribute to meaningful work and be part of an organization that truly believes when you win, we all win, and when you fail, we all learn, then we’re eager to hear from you.
The achievers and courageous challenge-crushers we seek, have the following characteristics and skills:
Position Responsibilities: Design and implement scalable, fault-tolerant data pipelines to process
both batch and streaming data. Develop data lake and warehouse solutions leveraging services like
Snowflake for highperformance analytical processing. Perform advanced data modeling and
optimization, including dimensional modeling, partitioning, clustering, and indexing to ensure
efficient data access. Enable realtime analytics and monitoring by building low-latency, event-
driven pipelines and integrating with visualization and alerting platforms. Implement data quality
checks, data lineage tracking, and metadata management to maintain trust and traceability across
the organization. Collaborate cross-functionally with product, analytics, and data science teams to
translate business use cases into scalable data solutions. Define and enforce data contracts and data
SLAs, ensuring accuracy, timeliness, and compliance across data products. Create reusable
frameworks for ETL orchestration, schema validation, and pipeline testing to accelerate
development across teams. Treating datasets as reusable products with versioning, contracts, and
SLAs. Own KPI definitions and metrics logic, ensuring consistent reporting and analytics across
business units. Partner with senior stakeholders to define strategic data goals, such as customer
360, churn prediction, or marketing attribution models. Measure and improve data adoption and
impact, including usage tracking, performance benchmarking, and cost optimization. Conduct
technical interviews and contribute to the development of internal best practices and coding
standards.
Position Requirements: Master’s degree (or foreign equivalent) in Computer Engineering, or
related field, PLUS two (2) years of experience in the job offered or a related position. Experience
must include demonstrable knowledge of: Snowflake; DBT; Tableau; Python; Pandas; NumPy;
AirFlow; Shell scripting; PL/SQL; Postgres SQL, and; GitHub. Required knowledge may be
gained prior to or concurrently with Master’s degree. Travel to unanticipated client locations
throughout the U.S., approximately 30% as required. Any suitable combination of education,
training, or experience is acceptable.
Apply at careers.quest-global.com and reference Job Code 28290.0303
Pay Range: USD $140,712/year .
Compensation decisions are made based on factors including experience, skills, education, and other job-related factors, in accordance with our internal pay structure. We also offer a comprehensive benefits package, including health insurance, paid time off, and retirement plan.
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