Sr Analytics Data Engineer

We are seeking a Consultant, Analytic Engineering to join our growing team of experts. This senior role will focus on leading analytics initiatives, developing advanced data models, and creating sophisticated reporting frameworks that enable data-driven decision making. The ideal candidate will bridge the gap between data engineering and business intelligence, provide technical leadership, and mentor team members while working with modern analytics tools and cloud data platforms.

Key Responsibilities:

Analytics Development & Data Modeling:

Lead the development and maintenance of dimensional data models optimized for analytics and reporting.
Design and implement semantic layers and business logic using SQL.
Create and optimize advanced data transformations that support business intelligence requirements.
Implement comprehensive data quality checks and validation rules within analytics workflows.
Lead the development of metrics, KPIs, and business definitions.
Provide technical guidance on data modeling best practices and standards.

Reporting & Visualization:

Build and maintain advanced dashboards and reports using Power BI, Sigma Computing, Tableau or any client required tool.
Lead collaboration with business stakeholders to understand reporting requirements and translate them into technical solutions.
Design intuitive and performant visualizations that communicate complex insights effectively.
Manage report deployment, versioning, and documentation.
Optimize report performance and user experience.
Establish reporting standards and best practices for the team.

Platform & Tool Management:

Work with Snowflake and modern cloud data platforms to support analytics workloads.
Lead the management and configuration of BI tools and analytics platforms.
Implement and enforce best practices for report organization, security, and governance.
Drive data catalog and metadata management initiatives.
Evaluate and recommend new analytics tools and technologies.

Technical Leadership & Project Management:

Lead project teams when necessary (without direct reports) and provide technical leadership and guidance to team members.
Coordinate cross-functional teams and drive technical decisions.
Set the technical direction for analytics initiatives while mentoring others through project work.
Review and approve technical designs and implementations.
Manage project timelines, deliverables, and stakeholder expectations.

Client Collaboration & Support:

Partner with client teams to gather analytics requirements and clarify business needs.
Communicate technical concepts to non-technical stakeholders clearly and professionally.
Lead client meetings, demos, and training sessions.
Provide expert support for report troubleshooting and user questions.
Document solutions and create user guides for analytics deliverables.
Build and maintain strong client relationships.

Data Quality & Governance:

Implement and oversee data validation and testing frameworks for analytics models.
Ensure compliance with security and governance standards including RBAC and data access controls.
Lead documentation of data definitions, lineage, and business rules.
Drive data quality monitoring and issue resolution.
Establish data governance policies and procedures.

Team Collaboration & Growth:

Work closely with data engineers, analytics engineers and project managers to design solutions.
Lead code reviews and establish team standards and best practices.
Drive internal knowledge sharing and team learning sessions.
Develop reusable analytics templates and accelerators.
Mentor junior team members and support their professional development.

Continuous Learning
Stay current with analytics engineering tools, techniques, and industry trends.
Learn new features in Power BI, Sigma Computing, Tableau, and other analytics platforms.
Explore and implement emerging practices in metrics layers, semantic modeling, and analytics engineering.
Share knowledge and insights with the team.