Manager, Data Engineering & Analytics

V SHRED; United States; On-site; USD 170,000 - 190,000; Full time

Job summary

A health and fitness company in the United States is seeking a Manager for Data Engineering & Analytics. This role involves building and operating the organization’s data capabilities, ensuring the execution of data strategies and governance. The ideal candidate will have extensive experience in data engineering and analytics, including leadership skills, and must establish data governance and compliance practices. A strong understanding of modern cloud data architectures is required, along with the ability to communicate effectively with stakeholders.

Qualifications

• 7–10+ years of experience in data engineering, analytics, or data platform roles.
• 3+ years in a people management or leadership role.
• Strong understanding of cloud data architectures and analytics platforms.

Responsibilities

• Oversee the design and operation of the enterprise data platform.
• Ensure high data quality, availability, performance, and cost efficiency.
• Lead the application of advanced analytics and AI/ML.

Skills

Data architecture understanding

Stakeholder management

Communication skills

Tools

Snowflake

Fivetran

Dagster

dbt

Sigma

Job description

This range is provided by V SHRED. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.

Base pay range

$170,000.00/yr - $190,000.00/yr

V Shred is seeking a Manager, Data Engineering & Analytics who will be responsible for building, operating, and evolving the organization’s end-to-end data capabilities. This role owns the execution of the data strategy, and governance of data engineering, business intelligence, AI and advanced analytics, data management, and data compliance. The individual will act as both a hands‑on player‑coach of a small team, and a hands‑on partner to business and technology stakeholders, ensuring data is reliable, secure, compliant, and effectively leveraged to drive decision‑making and innovation.

This role is accountable for translating business needs into scalable data platforms, trusted insights, and advanced analytical solutions while establishing strong data governance and stewardship practices.

Key Responsibilities

• Oversee the design, build, and operation of the enterprise data platform, with Snowflake as the core analytical data warehouse.
• Own scalable, reliable data pipelines leveraging tools such as Fivetran and Dagster for ingestion, orchestration and workflow management.
• Ensure high data quality, availability, performance, and cost efficiency across all core data assets.
• Drive best practices for ELT/ETL, orchestration, data modeling, data observability, and incident management.
• Evaluate, select, and manage data tooling, cloud infrastructure, and vendor relationships.

Data Transformations & Modeling

• Establish transformation standards and analytics engineering practices using dbt.
• Ensure consistent, well‑documented data models that support both operational and analytical use cases.
• Promote testing, version control, and modular design for data transformations.

Business Intelligence & Reporting

• Own execution of BI and reporting capabilities, with Sigma as the primary BI layer.
• Ensure dashboards and reports are accurate, performant, and aligned with defined metrics and definitions.
• Support self‑service analytics by maintaining semantic layers and certified datasets.
• Partner with business teams to refine requirements and ensure insights are actionable.

AI, Advanced Analytics & Experimentation

• Lead the application of advanced analytics, statistical modeling, and AI/ML where they create clear business value.
• Collaborate with growth, performance marketing and engineering teams to embed analytics and AI into products, experimentation, and decision workflows.
• Establish standards for model development, validation, monitoring, and lifecycle management.

Marketing Data & Attribution

• Support analytics use cases related to marketing performance, attribution, and growth measurement.
• Oversee integrations with advertising and marketing platforms like Google, Meta, TikTok etc.
• Partner with Marketing and Performance Marketing teams to improve attribution models, funnel analysis, and ROI measurement.
• Ensure marketing data is well‑modeled, governed, and trusted for decision‑making.

Data Governance, Management & Compliance

• Establish and enforce data governance frameworks covering data ownership, stewardship, quality, lineage, and documentation.
• Ensure compliance with applicable regulations and standards including GDPR, CCPA, SOC2 etc.
• Partner with Legal, Security to manage data access, retention, and risk.
• Oversee master data management and metadata management practices.

Operational Excellence

• Implement intake, prioritization, and delivery processes for data initiatives.
• Manage capacity planning, and team resourcing for the data pillar.
• Continuously improve reliability, scalability, and efficiency of data operations through automation and standardization.

Qualifications

Required

• 7–10+ years of experience in data engineering, analytics, or data platform roles, with 3+ years in a people management or leadership role.
• Strong understanding of modern cloud data architectures and analytics platforms.
• Proven experience delivering enterprise BI and analytics solutions.
• Demonstrated ability to establish data governance, data quality, and compliance practices.
• Strong stakeholder management and communication skills.

Preferred

• Hands‑on experience with Snowflake as an enterprise data warehouse.
• Experience building pipelines using Fivetran and orchestrating workflows with Dagster.
• Strong analytics engineering background using dbt.
• Knowledge of marketing analytics, attribution models, and ad platform integrations.
• Experience operating data platforms in high‑growth or complex environments.
• Strategic thinker with a strong bias toward execution.
• Pragmatic leader who balances speed, quality, cost, and risk.
• Able to influence across technical and non‑technical stakeholders.
• Clear communicator who can simplify complex data topics.
• Passion for building scalable data foundations and high‑performing teams.

Seniority level: Mid‑Senior level

Employment type: Full‑time

Industries: Wellness and Fitness Services