Manager of Data Engineering and Analytics Consulting

We’re hiring a Manager of Data Engineering & Analytics Consulting!

Employment type:

Full Time/Direct Hire Only (No Agencies)

Location:

Atlanta GA Metro, Washington DC Metro, Charlotte Metro, NYC, or Richmond, VA

Location Type:
Hybrid - Home Office/Local Ippon office (1-2 days per week onsite)

The Ippon story started in 2002 in Paris, France - cue in the accordion. Our founder and CEO Stéphane Nomis used his unique experience as an international Judo champion to create a culture based on the sports values of ambition and excellence. Our USA Headquarters office is located in Richmond, VA, with additional offices in New York, NY, Washington DC, and Atlanta, GA.

We are a technology consulting firm that specializes in helping accelerate our client’s digital roadmap in the areas of Product Management, Cloud, Data, and Software Engineering. Our culture and reputation is driven by our COACH values; our Ipponites are Collaborative, Open-minded, Adaptable, Courageous, and Hungry.

The Manager of Data Engineering & Analytics Consulting leads project delivery, strengthens client relationships, and leads team development. This role blends technical leadership with people management, ensuring high-quality, on-time solutions that drive business value. The Manager also mentors consultants, supports pre-sales, and translates complex needs into practical data solutions across cloud, engineering, and analytics. Ideal for a results-driven, client-focused leader passionate about impact and growth.

• Project Delivery & Technical Leadership:
• Lead and oversee the successful delivery of data engineering and analytics projects, ensuring outcomes align with client goals and contractual obligations
• Act as a hands-on contributor when needed, helping architect and implement data solutions across cloud platforms such as Snowflake.
• Support pre-sales efforts by participating in scoping calls, developing proposals, estimating effort, and presenting technical solutions to prospective clients
• Contribute to internal initiatives such as playbook development, accelerator design, or knowledge sharing to improve delivery efficiency and consistency
• Help drive continuous improvement by providing feedback on processes, tools, and methodologies across the practice
• Travel to client sites as needed, generally within the US, with an expectation of occasional multi-day trips depending on engagement needs

• Client & Team Development:
• Serve as the primary point of contact for client stakeholders, building trusted relationships and ensuring high levels of satisfaction throughout engagements
• Mentor, manage and develop consultants on both technical and consulting competencies, fostering a high-performing, collaborative team culture
• Identify upsell or cross-sell opportunities during delivery and collaborate with Client Success or Sales teams to convert them into formal engagements
• Represent the firm at industry events, meetups, or conferences to expand your network and promote the practice

• Minimum Requirements:
• 5+ years of experience in data engineering, analytics, or data consulting, with proven success in client-facing and delivery roles
• 3+ years of experience in modern cloud data platforms with an emphasis on Snowflake, in addition to familiarity with Databricks, Azure Synapse, or AWS Redshift
• 3+ years of experience with AWS-native ETL tools such as Glue, EMR, and Step Functions
• Demonstrated ability to lead project delivery, manage small technical teams, and translate business needs into scalable data solutions
• Willingness to travel for client engagements as needed

• Preferred Requirements:
• Prior experience in a consulting or professional services environment
• Familiarity with complex AWS environments and services such as S3, Athena, IAM, Lambda, Step Functions, Secrets Manager, API Gateway, SQS, SNS, Kinesis, DMS, Glue, and Direct Connect
• Experience supporting pre-sales efforts, including proposal development, scoping, and technical demos
• Exposure to data governance, quality frameworks, or enterprise data strategy initiatives
• Familiarity with AI/ML pipelines or integrating ML models into…