Senior Data Engineer - Data & Analytics

Senior Data Engineer 

Data & Analytics 

About the Role 

We are hiring a Senior Data Engineer to shape and strengthen the data foundation that drives company performance. 

This is a senior individual contributor role with meaningful influence. You will define engineering standards, evolve our data platform, and ensure data is reliably integrated and structured to support confident decision making across the organization. 

Success in this role requires more than technical execution. You will be expected to operate independently, bring structure to ambiguity, challenge unclear assumptions, and translate complex system and business problems into durable data solutions. 

Key Responsibilities 

Data Platform Leadership 

• Lead the development and continuous improvement of data pipelines and integration frameworks 

• Define standards for ingestion, orchestration, and data movement across the platform 

• Improve reliability, performance, and cost efficiency of data pipelines and storage 

• Design scalable, reusable patterns that support consistent data flow across systems 

Data Integration and Architecture 

• Design and implement integrations across internal and external systems using tools such as Fivetran and custom pipelines 

• Own how data enters and moves through the warehouse, ensuring consistency and integrity 

• Structure data layers to support both upstream flexibility and downstream consumption 

• Ensure strong alignment between source system logic and warehouse representations 

Data Modeling and Foundation 

• Architect and implement core data models in Snowflake using dbt 

• Build durable data layers aligned to core revenue and operational domains 

• Ensure strong alignment between upstream data structures and downstream reporting needs 

• Embed testing, documentation, and performance optimization into standard engineering practice 

Data Reliability and Quality 

• Establish and enforce data quality standards across ingestion and transformation layers 

• Design systems for validation, monitoring, and lineage 

• Proactively identify and resolve data issues, reducing ambiguity and downstream impact 

• Strengthen trust in enterprise data through consistent and reliable delivery 

AI-Enabled Data Systems 

• Treat AI as a core capability in modern data engineering, leveraging it to deliver high-quality solutions with greater speed and rigor 

• Design data pipelines and structures that enable safe and effective use of AI with trusted data 

• Integrate AI into engineering workflows to accelerate development, monitoring, and optimization 

• Apply disciplined judgment when evaluating AI-generated outputs, ensuring enterprise standards for accuracy and consistency 

• Establish practical guardrails for responsible AI usage across both engineering and business consumption 

Cross-Functional Partnership 

• Translate complex and ambiguous business questions into scalable data solutions 

• Communicate technical tradeoffs clearly to both technical and business stakeholders 

• Introduce platform and process improvements and drive them through implementation 

• Influence data standards across the Data & Analytics function 

What We Look For 

• Ability to operate independently in complex, evolving environments 

• Clear and structured communication 

• Strong analytical reasoning and systems thinking 

• Ownership mindset with focus on measurable business outcomes 

• Willingness to challenge assumptions constructively 

• High standards for data quality, reliability, and engineering rigor 

Qualifications 

• 6+ years of experience in data engineering or analytics engineering 

• Strong experience with data integration, pipeline development, and warehouse architecture 

• Strong hands-on experience with Snowflake and dbt 

• Experience with data integration tools such as Fivetran 

• Experience working with cloud platforms such as AWS 

• Advanced SQL with demonstrated performance tuning expertise 

• Experience with Git-based workflows and GitHub for version control 

• Experience building and operating reliable data pipelines 

Preferred: 

• Experience in SaaS or subscription-based businesses 

• Experience working with global stakeholders 

• Python for automation or platform tooling 

Impact 

The systems and standards established in this role will directly influence data reliability, operational efficiency, and decision making. The quality of this foundation will determine how effectively the organization leverages both trusted data and AI to drive performance.