Senior Data Engineer – Business Intelligence
CEI Group
Burlington, MA
Senior Data Engineer – Business Intelligence
About the Role
We’re seeking a Senior Data Engineer to help design, build, and evolve our Enterprise Data Operating Architecture, the backbone of business intelligence, analytics, and data-driven decision-making across the organization.
You’ll develop scalable data pipelines, models, and services to ensure trusted, timely, and business-aligned data is available where decisions are made. This role is both hands-on and strategic, working closely with analysts, product teams, and business stakeholders to transform complex questions into reliable, actionable insights.
As we move toward AI-enabled operations, you’ll play a critical part in defining and advancing our data engineering practices.
Key Responsibilities
Data Architecture & Engineering
Design, build, and optimize scalable data pipelines using ELT and streaming patterns.
Develop and enhance enterprise data models that support reporting and analytics.
Ensure high data availability, reliability, and performance across all platforms.
Enterprise Intelligence Enablement
Partner with analysts and business teams to refine data requirements and definitions.
Contribute to metric design, lineage tracking, and semantic consistency.
Troubleshoot and resolve data quality and integration issues quickly and effectively.
Platform Maturity & Digital Enablement
Automate ingestion and transformation workflows to minimize manual work.
Maintain strict data security, privacy, and compliance controls.
Improve data governance, cataloging, and observability processes.
Continuous Improvement
Develop and share standard methodologies, documentation, and reusable components.
Mentor and support junior engineers and cross-functional peers.
Drive initiatives aligned with our guiding principles:
Human-centric enablement
Trusted data and governance by design
Adaptive operations
Intentional automation
Systems that scale as one
Qualifications
Required:
5–8 years of professional experience as a Data Engineer.
Strong SQL and Python skills, with experience in cloud-native data environments.
Hands-on experience with Snowflake, dbt, and modern ELT/streaming pipelines.
Solid understanding of data modeling techniques (dimensional, event-based, etc.).
Proven ability to collaborate across technical and business teams.
Preferred:
Experience in SaaS, product usage analytics, or operational data modeling.
Familiarity with workflow orchestration and data observability tools.
Exposure to real-time data pipelines or machine learning feature engineering.