Senior Manager, Data Engineering

NinjaHoldings

. Lead the Data Engineering team and set the technical direction for the data platform .

Posted 10/6/2026full-timeRemote • Illinois • United StatesSenior💰 $135,000 - $175,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in leading Data Engineering teams and setting technical direction for data platforms, with a strong focus on Snowflake, PostgreSQL, and modern data architectures. Capable of establishing engineering practices around data quality, automated testing, and observability while effectively communicating technical decisions across diverse teams.

Highest-signal resume keywords

Data Engineering LeadershipSnowflake ExpertisePostgreSQL ProficiencyModern ELT/ETL ArchitecturesData Quality and Governance

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data EngineeringDatabase EngineeringSQLDimensional ModelingData IngestionAutomated TestingData QualityCloud Data PlatformsAI ApplicationsData Catalogs

Soft Skills

Strong CommunicationTeam LeadershipCross-Functional Collaboration

Tools & Technologies

DbtFivetranMeltanoAWSMedallion Architecture

Industry Keywords

Financial ServicesRegulated Industry

Tech Stack

Tools & technologies

AWSCloudETLPostgresPythonRubySQL

About the role

Key responsibilities & impact

Lead the Data Engineering team and set the technical direction for the data platform
Own the architecture, reliability, performance, and evolution of Snowflake, PostgreSQL, and data pipelines
Lead the transition to a Medallion architecture and establish standards for data ingestion, transformation, modeling, testing, documentation, and consumption
Own and evolve the modern data stack, including Snowflake, dbt, Fivetran, Meltano, PostgreSQL, AWS, and related technologies
Partner with application engineering teams on transactional database design, schema changes, performance, scalability, and reliability
Work with Engineering, Analytics, Product, Finance, Risk, Marketing, and other business teams to turn data needs into reusable solutions
Establish engineering practices around data quality, automated testing, observability, lineage, security, documentation, and incident response
Improve self-service access to data
Monitor and optimize the platform for performance, scalability, and cost
Build a long-term roadmap balancing current business needs with future platform needs, including AI use cases
Lead, mentor, and develop a strong team of Data Engineers
Set technical standards and expectations while giving engineers ownership
Participate in architecture and design decisions and provide technical support when needed
Help prioritize work based on business impact, technical risk, reliability, and long-term value
Create a culture of data quality, testing, documentation, and operational reliability
Communicate technical decisions, tradeoffs, risks, and investments to technical and nontechnical teams

Requirements

What you’ll need

6+ years of experience in Data Engineering, Data Platform Engineering, Database Engineering, or a related field
2+ years of experience leading or managing Data Engineers or other technical teams
Strong experience with Snowflake, dbt, SQL, and modern ELT or ETL architectures
Strong understanding of PostgreSQL or similar relational databases, including schema design, indexing, query performance, and reliability
Experience with data ingestion and integration tools such as Fivetran, Meltano, or similar technologies
Experience with dimensional modeling, Medallion architecture, or other modern warehouse design patterns
Strong understanding of data quality, automated testing, observability, lineage, governance, and security
Experience operating cloud based data platforms and understanding performance and cost tradeoffs
Ability to think at both the architecture level and the implementation level when needed
Strong communication skills and the ability to work effectively across Engineering, Analytics, business teams, and leadership
Experience with Python or Ruby for automation, tooling, or data processing
Experience in financial services or another regulated industry
Experience supporting analytics or AI applications
Experience with data catalogs, data contracts, or master data management
Experience leading a significant warehouse or data platform modernization effort
Experience using AI and automation to improve engineering productivity, monitoring, documentation, or data quality

Benefits

Comp & perks

Flexible Paid Time Off
Health Benefits with generous medical, dental and vision insurance plans
401(k) with matching contribution
Paid Family Leave
Annual Wellness & WFH Subsidies
Employee Referral Program
Remote first culture with convenient downtown office in the heart of the city