Senior Manager, Data Engineering

KIPP Foundation

. Own and drive end-to-end delivery of data architecture and pipeline solutions, including planning, requirements gathering, design, build, and testing .

Posted 9/21/2026full-timeRemote • United StatesSenior💰 $120,000 - $145,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in data architecture, pipeline solutions, and MLOps, with a strong focus on project management, agile methodologies, and team leadership. Proficient in SQL, Spark, and cloud-based data platforms, ensuring high-quality data solutions and operational efficiency.

Highest-signal resume keywords

Data Architecture ManagementMLOps ImplementationAgile Sprint OperationsSQL and Spark ProficiencyTeam Development and Coaching

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

SQLSparkPySparkETL/Data PipelinesCI/CDData Quality FrameworkMachine Learning PrinciplesVersion ControlData Platform ManagementAgile Project Management

Soft Skills

Problem-SolvingInitiativeRisk AnticipationEffective DelegationCommunication

Tools & Technologies

JIRAGitBitbucketGitHubAzure DevOpsSnowflakeDatabricksFabric/OneLakeSSIS

Industry Keywords

Data EngineeringInfrastructure EngineeringCloud-Based Data PlatformsData WarehouseData Lakehouse

Tech Stack

Tools & technologies

AzureCloudETLPySparkSparkSQLSSIS

About the role

Key responsibilities & impact

Own and drive end-to-end delivery of data architecture and pipeline solutions, including planning, requirements gathering, design, build, and testing
Design and evolve the semantic layer as a governed single source of truth for business intelligence and reporting
Lead sprint planning and operations, including sprint execution, release planning, release delivery, dependency resolution, and blocker removal
Track and analyze sprint delivery metrics, operational efficiency, and DevOps performance to support continuous improvement
Design and operationalize a data quality framework with monitoring, alerting, root cause analysis, troubleshooting, resolution, and impact assessments
Establish foundational MLOps, machine learning, feature engineering, and ML/AI platform integration capabilities
Manage and continuously improve data architecture and pipelines, monitoring standards, and operational controls
Partner with Analytics, Application Development, Data Collection Strategy & Operations, IT Operations, Product Management, and Regional Data Systems & Strategy teams
Create, drive, track, and execute project plans while managing competing priorities
Maintain transparency into progress, risks, and dependencies through consistent tracking and communication
Guide team members in developing data solutions, data quality practices, review standards, and documentation
Manage and develop one or more employees or contractors through expectations, feedback, and coaching
Report to the Senior Director of Data Management & Governance

Requirements

What you’ll need

Passion and commitment to KIPP’s mission and ability to uphold KIPP’s Core Values
Demonstrated ability to co-create ambitious goals, monitor progress across multiple workstreams, and drive outcomes
Ability to create and execute project plans, manage competing priorities, delegate effectively, and maintain knowledge management systems
Ability to build and maintain processes aligned with organizational priorities
Problem-solving skills, initiative, risk anticipation, and proactive solution development
Experience developing and coaching teammates and managing performance and development goals
Knowledge and skills in SQL, Spark, PySpark, on-premises and cloud-based data platform management and architecture, CI/CD, ETL/data pipelines, version control, SSIS, agile sprint operations, project management tools, and machine learning principles
8+ years of professional experience in data engineering, infrastructure engineering, or a closely related technical field
Experience with SQL-based data platforms and modern cloud-based data warehouse/lakehouse platforms such as Fabric/OneLake, Snowflake, or Databricks
Experience managing agile sprint operations, DevOps metrics, and proficiency in JIRA or similar tools
Experience with version control and CI/CD workflows using Git and platforms such as Bitbucket, GitHub, and Azure DevOps
Strong technical proficiency in SSIS, Spark, PySpark, and SQL
Experience managing data platform operations and building/managing ETLs and pipelines
Experience managing and mentoring data engineers
Understanding of ML workflows and ML/AI enablement for data platforms
Bachelor’s degree in data engineering, computer science, or a related field

Benefits

Comp & perks

25 holidays
18 days additional flexible PTO days, increasing to 23 days for years 3 and 4 and to 28 days for years 5+
100% paid parental leave
100% coverage of the premium for employee medical/dental/vision plans
75% coverage of the premium for employee + family medical/dental/vision plans
Wellness benefits including fitness reimbursements, discounted tickets to theme parks/attractions, backup care support for children and adults/elders, and an employee assistance program
401K retirement plan with 4% match
Employer-sponsored legal plans
Life/disability insurance
Flexible spending accounts
Low travel requirement: 10% (20 days per year)