Analytics Engineering Manager

Description

Engagement Type: Contract-to-Hire (C2H)
Initial Engagement: Contract (6 months)
Conversion Opportunity: Potential full-time employment based on performance, mutual fit, and business requirements.

About the Role:

We are looking for a hands-on Analytics Engineering Manager to lead our analytics and BI engineering function and drive the evolution of our existing business intelligence landscape toward a modern, scalable, data-platform-driven analytics ecosystem.

This is a unique opportunity for an experienced analytics engineering professional who combines strong technical capabilities with team leadership, execution, and a forward-looking mindset toward AI-enabled analytics.

The successful candidate will lead a small team of BI engineers, own the delivery and reliability of our existing analytics solutions, and progressively modernize our BI landscape.

Beyond traditional BI modernization, this role will play an important part in aligning analytics engineering with our broader AI-first data platform strategy. This includes preparing analytical assets to support emerging AI-driven use cases, natural language analytics, and agentic data consumption patterns.

This is a player-coach role. We expect the candidate to remain deeply hands-on with solution design, development, troubleshooting, and implementation while providing technical direction, mentoring the team, and managing delivery.

The position offers an opportunity to grow from leading analytics engineering into broader data platform engineering leadership as the organization's platform capabilities and engineering responsibilities expand.

Key Responsibilities:

1. Analytics Engineering & Technical Leadership

• Lead the design, development, and maintenance of enterprise analytics solutions, reporting datasets, dashboards, and analytical applications.
• Establish engineering standards and best practices for analytics development, including SQL development, data modeling, performance optimization, testing, and deployment.
• Design scalable and reusable analytical data models, ensuring consistency of business definitions, metrics, and KPIs across different reporting and consumption channels.
• Remain hands-on in developing complex SQL transformations, analytical datasets, data pipelines, and BI solutions.
• Identify opportunities to simplify the analytics technology landscape and reduce technical debt.

2. BI Modernization & Data Platform Transition

• Lead the gradual modernization of the existing BI ecosystem, which includes legacy SQL Server reporting solutions, Dundas, Cognos, and BIRT.
• Modernize existing reporting solutions while ensuring business continuity, data accuracy, and minimal disruption to existing consumers.

3. Team Leadership & Engineering Management

• Lead, mentor, and develop a small team of analytics/BI engineers.
• Establish engineering ownership, development standards, code review practices, and quality expectations across the team.
• Manage priorities, delivery commitments, technical dependencies, and resource allocation.
• Build a culture of engineering excellence, accountability, collaboration, and continuous improvement.
• Identify skill gaps and develop team capabilities to transition from traditional BI development toward modern analytics engineering.
• Work closely with product, data engineering, AI, and business stakeholders to understand requirements and translate them into scalable technical solutions.
• Optimize complex SQL queries, data transformations,and analytical workloads.

What Success Looks Like:

The successful candidate will:

• Take ownership of the existing BI engineering function and ensure reliable delivery of current reporting and analytics requirements.
• Establish strong technical ownership and engineering practices within the team.
• Gradually transition reporting and analytics workloads toward reusable, governed data-platform assets.
• Reduce duplication of business logic and KPI definitions across reporting solutions.
• Improve the quality, performance, maintainability, and scalability of analytics solutions.
• Help prepare the analytics ecosystem for AI-driven and agentic consumption patterns.
• Build a technically capable team that can operate effectively within a modern data platform ecosystem.
• Demonstrate the technical breadth and leadership capabilities required to take ownership of broader data platform engineering responsibilities

Requirements

Technical Skills & Experience:

• 8+ years of experience in BI engineering, analytics engineering, data engineering, or related disciplines.
• 2+ years of experience leading technical teams, mentoring engineers, or managing engineering delivery.
• Strong hands-on expertise in SQL, including complex queries, analytical transformations, performance tuning, and data modeling.
• Experience with enterprise BI platforms such as Amazon QuickSight, Power BI, Tableau, Cognos, or comparable technologies. Additional preference is given to someone having experience on Dundas and Logi SaaS BI tools.
• Experience with modern data warehousing and cloud-based data platforms.
• Strong understanding of dimensional modeling, analytical data modeling, data marts, and reusable data models.
• Ability to balance technical execution, architectural thinking, and team leadership.