We are seeking Senior Analytics Engineer to work on a team at our client site in Manhattan. This role is contract to hire. While working for Roth Staffing (Ledgent Tech is a division of Roth), the W2 rate range is $58.61 to $91.15. The conversion salary is 121,900 to $189,600.
No 3rd party candidates can be considered for this role.
Role Summary
Marketing department is seeking an experienced Business Intelligence professional to join the Marketing Analytics organization as a Senior Analytics Engineer (Business Intelligence). This role builds complex dashboards and automated reporting solutions, translates stakeholder questions into technical specifications, and ensures reporting outputs are accurate, well-designed, and aligned to definitional standards.
At the Senior level, this role is expected to operate with general alignment, independently drive BI deliverables end-to-end, and serve as a go-to partner for stakeholders who need reliable reporting, strong visualization, and clear interpretation of results.
Key Responsibilities
Design and build complex dashboards with interactive features and strong visualization best practices (chart selection, usability, and stakeholder clarity).
Develop and maintain complex SQL queries and Python-based automation to support reliable data extraction, transformation, QA checks, and scheduled reporting delivery; maintain shared codebases in version control (e.g., Git, Azure DevOps), following team standards for commits, reviews, and documentation.
Implement automated reporting pipelines and repeatable delivery patterns that reduce manual effort and improve reliability.
Independently source and integrate datasets; document data lineage and identify gaps, inconsistencies, or definitional misalignment.
Clarify vague requirements by asking the right questions, proposing visualization approaches, and aligning scope and success criteria with stakeholders.
Partner with Marketing and enterprise stakeholders to support MarTech data acquisition strategies (e.g., tagging/collection requirements, platform integrations) and improve availability and usability of marketing platform datasets for reporting and analytics.
Perform strong self-QA and milestone reviews to ensure accuracy in filters, calculations, and alignment to definitional standards.
Present BI outputs and insights to stakeholders with clear narrative framing, explaining assumptions, limitations, and tradeoffs.
Mentor entry-level BI engineers on tools, best practices, documentation, and stakeholder communication.
Manage projects concurrently, accurately scoping timelines and proactively flagging risks.
Growth mindset: receptive to feedback, proactive about learning, and continuously improves BI craftsmanship (accuracy, usability, documentation) through iteration.
Required Qualifications
Bachelor's degree in Computer Science, Data Analytics, Information Systems, Business Intelligence, or related field.
5+ years of experience in BI / analytics engineering or a closely related domain (may be adjusted, in whole or in part, at the Company's discretion, where a candidate demonstrates exceptional aptitude in other core skill areas).
Expert SQL; advanced experience with BI tools (Tableau/Power BI/Looker).
Strong knowledge of reporting standards, metric definitions, and dashboard usability principles.
Strong communication skills with experience translating stakeholder needs into technical specifications.
Preferred Qualifications
Master's degree in Data Analytics, Business Intelligence, Computer Science, or related field.
7+ years of experience in BI / analytics engineering or a closely related domain.
Experience with semantic layer concepts (e.g., LookML / MetricFlow) and workflow orchestration basics.
Relevant certifications (examples): Tableau Desktop Certified Professional; Microsoft Certified: Power BI Data Analyst Associate; dbt Analytics Engineering Certification; Snowflake SnowPro Advanced.
Experience using AI tools to improve workflow productivity (e.g., accelerating research, summarization, analysis, documentation, and automation).
Experience with marketing analytics and MarTech data sources, including tagging and web analytics (e.g., Google Analytics) and marketing platform data (e.g., ad buying platforms such as Campaign Manager 360 (CM360) / Search Ads 360 (SA360) and CRM tools such as Salesforce).
Experience in Property & Casualty (P&C) insurance is preferred.